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Seshadri S, Pudhukudi S, Vajiravelu J, Saravanan P, Hyett J, Ram U. Development of a semi-automated tool to measure fetal abdominal wall thickness during ultrasound at 20 weeks' gestation. Int J Gynaecol Obstet 2024. [PMID: 38607348 DOI: 10.1002/ijgo.15524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2023] [Revised: 02/27/2024] [Accepted: 03/24/2024] [Indexed: 04/13/2024]
Abstract
OBJECTIVES To develop a semi-automated tool for measuring fetal abdominal wall thickness (AWT). To validate the software using images captured by other centers and create a nomogram for fetal AWT between 18 and 20 weeks. METHODS A semiautomated tool that measured AWT was developed using images captured at the routine 20-week morphology scan. The software was developed using digital images captured routinely during scans of low-risk women. Inter- and intraobserver reliability was assessed between manual and semi-automated measures. The tool was validated using images acquired from other centers. Linear regression and quadratic polynomials were used to create a nomogram for AWT. RESULTS The semi-automated tool was able to measure AWT in all images. Interoperator reliability was 0.90 and 0.97 (P < 0.05) for manual and semi-automated methods, respectively. Measurement agreement varied between three operators from moderate to excellent (0.77, 0.87, 0.92), with overall agreement being good (0.85). The tool could be successfully applied to 89% of images from other centers. A nomogram was generated for AWT measurements of fetuses at 18-20 weeks in normal, low risk mothers. CONCLUSION Semi-automated measurement of AWT was feasible using images captured during the routine 20-week scan. This approach had lower inter- and intraobserver variability compared to manual measurement.
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Affiliation(s)
| | - Sindhu Pudhukudi
- Mediscan Systems, Chennai, India
- Aster Fetal Medicine, Aster Medcity, Cochin, India
| | | | - Ponnusamy Saravanan
- Populations, Evidence and Technologies, Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, UK
- Department of Diabetes, Endocrinology and Metabolism, George Eliot Hospital, Nuneaton, UK
| | - Jon Hyett
- Faculty of Medicine, University of Sydney, Sydney, New South Wales, Australia
| | - Uma Ram
- Seethapathy Clinic and Hospital, Chennai, India
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Nguyen-Hoang L, Papastefanou I, Sahota DS, Pooh RK, Zheng M, Chaiyasit N, Tokunaka M, Shaw SW, Seshadri S, Choolani M, Yapan P, Sim WS, Poon LC. Evaluation of screening performance of first-trimester competing-risks prediction model for small-for-gestational age in Asian population. Ultrasound Obstet Gynecol 2024; 63:331-341. [PMID: 37552550 DOI: 10.1002/uog.27447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Revised: 06/17/2023] [Accepted: 07/21/2023] [Indexed: 08/10/2023]
Abstract
OBJECTIVE To examine the external validity of the Fetal Medicine Foundation (FMF) competing-risks model for the prediction of small-for-gestational age (SGA) at 11-14 weeks' gestation in an Asian population. METHODS This was a secondary analysis of a multicenter prospective cohort study in 10 120 women with a singleton pregnancy undergoing routine assessment at 11-14 weeks' gestation. We applied the FMF competing-risks model for the first-trimester prediction of SGA, combining maternal characteristics and medical history with measurements of mean arterial pressure (MAP), uterine artery pulsatility index (UtA-PI) and serum placental growth factor (PlGF) concentration. We calculated risks for different cut-offs of birth-weight percentile (< 10th , < 5th or < 3rd percentile) and gestational age at delivery (< 37 weeks (preterm SGA) or SGA at any gestational age). Predictive performance was examined in terms of discrimination and calibration. RESULTS The predictive performance of the competing-risks model for SGA was similar to that reported in the original FMF study. Specifically, the combination of maternal factors with MAP, UtA-PI and PlGF yielded the best performance for the prediction of preterm SGA with birth weight < 10th percentile (SGA < 10th ) and preterm SGA with birth weight < 5th percentile (SGA < 5th ), with areas under the receiver-operating-characteristics curve (AUCs) of 0.765 (95% CI, 0.720-0.809) and 0.789 (95% CI, 0.736-0.841), respectively. Combining maternal factors with MAP and PlGF yielded the best model for predicting preterm SGA with birth weight < 3rd percentile (SGA < 3rd ) (AUC, 0.797 (95% CI, 0.744-0.850)). After excluding cases with pre-eclampsia, the combination of maternal factors with MAP, UtA-PI and PlGF yielded the best performance for the prediction of preterm SGA < 10th and preterm SGA < 5th , with AUCs of 0.743 (95% CI, 0.691-0.795) and 0.762 (95% CI, 0.700-0.824), respectively. However, the best model for predicting preterm SGA < 3rd without pre-eclampsia was the combination of maternal factors and PlGF (AUC, 0.786 (95% CI, 0.723-0.849)). The FMF competing-risks model including maternal factors, MAP, UtA-PI and PlGF achieved detection rates of 42.2%, 47.3% and 48.1%, at a fixed false-positive rate of 10%, for the prediction of preterm SGA < 10th , preterm SGA < 5th and preterm SGA < 3rd , respectively. The calibration of the model was satisfactory. CONCLUSION The screening performance of the FMF first-trimester competing-risks model for SGA in a large, independent cohort of Asian women is comparable with that reported in the original FMF study in a mixed European population. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
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Affiliation(s)
- L Nguyen-Hoang
- Department of Obstetrics and Gynaecology, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong SAR
| | - I Papastefanou
- Fetal Medicine Research Institute, King's College Hospital, London, UK
- Department of Women and Children's Health, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - D S Sahota
- Department of Obstetrics and Gynaecology, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong SAR
| | - R K Pooh
- CRIFM Prenatal Medical Clinic, Osaka, Japan
| | - M Zheng
- Center for Obstetrics and Gynecology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - N Chaiyasit
- Department of Obstetrics and Gynecology, King Chulalongkorn Memorial Hospital, Bangkok, Thailand
| | - M Tokunaka
- Department of Obstetrics and Gynecology, Showa University Hospital, Tokyo, Japan
| | - S W Shaw
- Department of Obstetrics and Gynecology, Taipei Chang Gung Memorial Hospital, Taipei, Taiwan
| | | | - M Choolani
- Department of Obstetrics and Gynecology, National University Hospital, Singapore
| | - P Yapan
- Faculty of Medicine, Siriraj Hospital, Bangkok, Thailand
| | - W S Sim
- Maternal-Fetal Medicine, KK Women's and Children's Hospital, Singapore
| | - L C Poon
- Department of Obstetrics and Gynaecology, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong SAR
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Jojo N, Nattala P, Seshadri S, Krishnakumar P, Thomas S. Knowledge of sexual abuse and resistance ability among children with intellectual disability. Child Abuse Negl 2023; 136:105985. [PMID: 36603444 DOI: 10.1016/j.chiabu.2022.105985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 11/18/2022] [Accepted: 11/27/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND Sexual abuse is a global concern among children with intellectual disabilities. Sexual abuse is frequent and long-lasting when the victim is a child with an intellectual disability. Moreover, the rate of sexual abuse is two to eight times the rate in the general population. OBJECTIVE This study aimed to investigate the knowledge of sexual abuse and resistance ability among children with intellectual disabilities. PARTICIPANTS AND SETTING The study was conducted among 120 children with mild or moderate intellectual disabilities attending twelve schools for specific purposes. METHODS We adopted a cross-sectional design to assess knowledge and resistance ability. Personal Safety Questionnaire and Modified What If Situation Test were administered verbally during individual interviews. Institutional Ethics Committee approved our study. RESULTS Current study suggests that children with intellectual disabilities have average knowledge (M = 6.6, SD = 1.6) regarding sexual abuse. More than 90 % of children demonstrated poor reporting skills. Although children exhibited good knowledge in differentiating appropriate from inappropriate touch requests, most children reported they would not disclose this incident to anyone. CONCLUSIONS This study strongly suggests the need for a structured training program for children with intellectual disabilities to prevent sexual abuse.
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Affiliation(s)
- N Jojo
- Faculty of Health, University of Canberra, Bruce, ACT, Australia.
| | - P Nattala
- Department of Nursing, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India
| | - S Seshadri
- Department of Child and Adolescent Psychiatry, NIMHANS, Bangalore, India
| | - P Krishnakumar
- Institute of Mental Health and Neurosciences (IMHANS), Kozhikode, Kerala, India
| | - S Thomas
- Department of Statistics, Christ University, Bangalore, India
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Halimeh R, Chronopoulou E, Duran M, Saab W, Serhal P, Seshadri S. P-399 Effect of male body mass index on miscarriage rate following fertility treatment, a systematic review and meta-analysis. Hum Reprod 2022. [DOI: 10.1093/humrep/deac107.376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Study question
Is raised paternal body mass index (BMI) important for the miscarriage rate following assisted reproductive technology (ART)?
Summary answer
Based on the available evidence, raised male BMI is not associated with higher risk of miscarriage following ART.
What is known already
More than half women and men of reproductive age worldwide are overweight or obese.There is extensive literature exploring the importance of normal female BMI for reproductive outcomes. However, little attention has been given to male BMI for couples seeking fertility treatment [1] .The adverse effect of male obesity on sperm parameters including DNA damage is well documented and there is evidence suggesting that raised male BMI results in significant decrease in live birth rate following ART [2] .Furthermore, emerging evidence from human and animal studies demonstrates that paternal obesity can affect the future health of the offspring through epigenetic pathways[3].
Study design, size, duration
A computerized literature search was performed using EMBASE, MEDLINE, CINAHL and the Cochrane Central register of trials from database inception to November 2021. The aim was to explore the association between male BMI on miscarriage rate following ART. Reference lists of relevant studies were cross-checked. Only articles with full manuscripts available and published in English were included. Papers not relating to human subjects were excluded. All eligible studies were included (observational, prospective and retrospective studies).
Participants/materials, setting, methods
Included studies reported on couples undergoing ART for any indication using partner’s fresh sperm. Outcomes of interest were miscarriage rate and clinical pregnancy rate. Outcome data from each study were pooled and expressed as odds ratio (OR) with 95% confidence interval (CI) by using a random-effect model due to statistical heterogeneity in the outcome data[4]. Heterogeneity of treatment effects was evaluated using the I2 statistic to quantify the variation across studies caused by heterogeneity.
Main results and the role of chance
Abstract screening identified 197 relevant studies. After excluding duplicates, reviews and studies which did not fulfill the inclusion criteria, full manuscripts were accessed for 13 studies. Six studies were identified exploring the effect of male BMI on miscarriage following ART, two prospective and four retrospective. The quality of evidence was low using the GRADE framework. Meta-analysis was possible for three studies including 6793 couples undergoing ART. Outcomes were compared for male BMI < 25 kg/m2 versus BMI >/=25 kg/m2 . The pooled results did not show a statistically significant increase in miscarriage rate when the male partner was overweight or obese compare to normoweight (OR 1.32, 95% CI 0.82–2.1, P = 0.249). There was significant heterogeneity between the included studies (I 2 = 48.7%). There was no significant effect of male BMI on clinical pregnancy rate (OR 0.90, 95% CI 0.59–1.38, P = 0.637). For two of the remaining studies which could not be included in the meta-analysis due to missing data, the authors concluded that male BMI >25 was not associated with increased miscarriage risk whilst the most recent prospective study showed that high male BMI was associated with increased risk of chromosomal aberration-related miscarriages.
Limitations, reasons for caution
The number of the included studies and significant heterogeneity are the main limitations. It was not possible to account for important confounders such as age, subfertility diagnosis, type of stimulation and laboratory parameters including embryo grade. We grouped participants in two BMI categories therefore did not distinguish between overweight/obesity/morbid obesity.
Wider implications of the findings
Despite increasing evidence suggestive of adverse effect of raised male BMI on reproductive outcomes, there is limited literature exploring the impact on miscarriage rate following ART. More well-designed studies are needed for sound conclusions. Paternal characteristics, general health and preconception lifestyle should not be overlooked in the fertility consultation.
Trial registration number
not applicable
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Affiliation(s)
- R Halimeh
- The Centre for Reproductive and Genetic Health, The Centre for Reproductive and Genetic Health CRGH- 230-232 Great Portland St- Fitzrovia- London- W1W 5QS- UK. , London, United Kingdom
| | - E Chronopoulou
- The Centre for Reproductive and Genetic Health, The Centre for Reproductive and Genetic Health CRGH- 230-232 Great Portland St- Fitzrovia- London- W1W 5QS- UK. , London, United Kingdom
| | - M Duran
- The Centre for Reproductive and Genetic Health, The Centre for Reproductive and Genetic Health CRGH- 230-232 Great Portland St- Fitzrovia- London- W1W 5QS- UK. , London, United Kingdom
| | - W Saab
- The Centre for Reproductive and Genetic Health, The Centre for Reproductive and Genetic Health CRGH- 230-232 Great Portland St- Fitzrovia- London- W1W 5QS- UK. , London, United Kingdom
| | - P Serhal
- The Centre for Reproductive and Genetic Health, The Centre for Reproductive and Genetic Health CRGH- 230-232 Great Portland St- Fitzrovia- London- W1W 5QS- UK. , London, United Kingdom
| | - S Seshadri
- The Centre for Reproductive and Genetic Health, The Centre for Reproductive and Genetic Health CRGH- 230-232 Great Portland St- Fitzrovia- London- W1W 5QS- UK. , London, United Kingdom
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Craze H, Odia R, Cawood S, Gaunt M, Seshadri S, Marvelos D, Saab W, Ozturk O, Serhal P. P-472 Extended oocyte cryostorage period is not associated with decreased post-warm survival rate: a retrospective study of 5208 vitrified/warmed oocytes at a single centre. Hum Reprod 2022. [DOI: 10.1093/humrep/deac107.444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Study question
Is extended oocyte cryostorage period associated with decreased post-warm survival rate?
Summary answer
There is a weak inverse correlation between oocyte cryostorage duration and post-warm survival (r = 0.09, p = 0.01). This equates clinically to a reduction of 0.0003% survival/day.
What is known already
It is widely reported that extended embryo storage is not associated with reduced post-warm survival rates, however there are no such studies in the literature relating to the effect of extended cryostorage duration on oocytes.
Successful outcomes from oocyte vitrification are related to reduced patient age however UK government regulations only permit those with a medical indication to store and use their gametes over 10 years.
With the intended extension of this 10-year limit, it is therefore fair for clinics to expect an increasing population of younger patients choosing to store their oocytes for longer periods.
Study design, size, duration
A retrospective audit of all vitrified/warmed oocyte cycles at a single centre from 2014-2021. A total of 5208 oocytes were included in the study, from 602 treatment cycles.
Participants/materials, setting, methods
Patients of all ages were included in the study. Data was obtained retrospectively from IDEAS V6.0 at CRGH, UK. All oocytes were vitrified/warmed according to the Irvine Scientific/Kitazato media protocols, with all other protocols excluded. Data was analysed using IBM® SPSS® Statistics V24. Kendall’s tau-b and Spearman’s Rho correlation coefficients measured the strength and direction of association between variables. A linear regression model was used to establish the effect of duration on survival per day.
Main results and the role of chance
The median age at oocyte vitrification was 31 years (range 18-45 years, LQR=25 years, UQR=37 years). There was a median of 8 oocytes thawed per case (LQR=6, UQR 11 oocytes) with a median of 6 oocytes surviving (LQR=3, UQR=9 oocytes). The median survival rate across all ages was 81% (LQR=58%, UQR=100%). There was no significant difference in oocyte survival rate between age categories (<35 years vs > 35 years; p = 0.137, n = 414 & 188 respectively). Increasing age was however, significantly correlated with fewer oocytes vitrified (r = 0.283, p = 0.001).
There is a weak inverse correlation between oocyte cryostorage duration and post-warm survival (r = 0.09). This correlation reaches statistical significance (p = 0.01), however this equates clinically to a reduction of 0.0003% survival rate per day.
No significant difference was observed in post-warm oocyte survival rate across duration of vitrification categories (≤3 years vs 4-5 years vs > 5 years; p = 0.154, n = 416, 141 & 45 cases respectively).
The median duration for which oocytes remained in cryostorage was 565 days (1.6 years) (LQR & UQR=233 days (0.64 years) and 1390 days (3.8 years) respectively).
Limitations, reasons for caution
Although retrospective, the study benefits from many cycles, all of which were carried out at the same unit, using the same vitrification/warming media protocol. Limitations of this study include a relatively short median cryostorage duration time which could be masking the true effect of duration on post-warm oocyte survival.
Wider implications of the findings
Following a public consultation in 2020 regarding the 10-year storage limit for gametes and embryos, the UK Government proposed changes the current legislation which will allow patients to extend cryostorage beyond 10 years without a medical indication. To our knowledge, this is the first study to lend support this movement.
Trial registration number
IRB-001C03-01-22
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Affiliation(s)
- H Craze
- CRGH, Embryology , LONDON, United Kingdom
| | - R Odia
- CRGH, Embryology , LONDON, United Kingdom
| | - S Cawood
- CRGH, Embryology , LONDON, United Kingdom
| | - M Gaunt
- CRGH, Embryology , LONDON, United Kingdom
| | - S Seshadri
- CRGH, Embryology , LONDON, United Kingdom
| | - D Marvelos
- CRGH, Embryology , LONDON, United Kingdom
| | - W Saab
- CRGH, Embryology , LONDON, United Kingdom
| | - O Ozturk
- CRGH, Embryology , LONDON, United Kingdom
| | - P Serhal
- CRGH, Embryology , LONDON, United Kingdom
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Gonzales MM, Garbarino VR, Marques Zilli E, Petersen RC, Kirkland JL, Tchkonia T, Musi N, Seshadri S, Craft S, Orr ME. Senolytic Therapy to Modulate the Progression of Alzheimer's Disease (SToMP-AD): A Pilot Clinical Trial. J Prev Alzheimers Dis 2022; 9:22-29. [PMID: 35098970 PMCID: PMC8612719 DOI: 10.14283/jpad.2021.62] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 07/25/2021] [Indexed: 12/13/2022]
Abstract
Preclinical studies indicate an age-associated accumulation of senescent cells across multiple organ systems. Emerging evidence suggests that tau protein accumulation, which closely correlates with cognitive decline in Alzheimer's disease and other tauopathies, drives cellular senescence in the brain. Pharmacologically clearing senescent cells in mouse models of tauopathy reduced brain pathogenesis. Compared to vehicle treated mice, intermittent senolytic administration reduced tau accumulation and neuroinflammation, preserved neuronal and synaptic density, restored aberrant cerebral blood flow, and reduced ventricular enlargement. Intermittent dosing of the senolytics, dasatinib plus quercetin, has shown an acceptable safety profile in clinical studies for other senescence-associated conditions. With these data, we proposed and herein describe the objectives and methods for a clinical vanguard study. This initial open-label clinical trial pilots an intermittent senolytic combination therapy of dasatinib plus quercetin in five older adults with early-stage Alzheimer's disease. The primary objective is to evaluate the central nervous system penetration of dasatinib and quercetin through analysis of cerebrospinal fluid collected at baseline and after 12 weeks of treatment. Further, through a series of secondary outcome measures to assess target engagement of the senolytic compounds and Alzheimer's disease-relevant cognitive, functional, and physical outcomes, we will collect preliminary data on safety, feasibility, and efficacy. The results of this study will be used to inform the development of a randomized, double-blind, placebo-controlled multicenter phase II trial to further explore of the safety, feasibility, and efficacy of senolytics for modulating the progression of Alzheimer's disease. Clinicaltrials.gov registration number and date: NCT04063124 (08/21/2019).
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Affiliation(s)
- Mitzi M. Gonzales
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, Department of Neurology, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78229 USA
| | - V. R. Garbarino
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, Department of Neurology, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78229 USA
| | - E. Marques Zilli
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, Department of Neurology, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78229 USA
| | | | - J. L. Kirkland
- Mayo Clinic, Robert and Arlene Kogod Center on Aging, Rochester, MN USA
| | - T. Tchkonia
- Mayo Clinic, Robert and Arlene Kogod Center on Aging, Rochester, MN USA
| | - N. Musi
- University of Texas Health Science Center at San Antonio, Barshop Institute for Longevity and Aging Studies, San Antonio Geriatric Research, Education and Clinical Center (GRECC), Department of Medicine, San Antonio, TX USA
| | - S. Seshadri
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, Department of Neurology, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78229 USA
- Boston University School of Medicine, Department of Neurology, Boston, MA USA
| | - S. Craft
- Wake Forest School of Medicine, Gerontology and Geriatric Medicine, 575 Patterson Avenue, Winston-Salem, NC 27101 USA
| | - Miranda E. Orr
- Wake Forest School of Medicine, Gerontology and Geriatric Medicine, 575 Patterson Avenue, Winston-Salem, NC 27101 USA
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Jacob M, O’Donnell A, Samra J, Gonzales M, Satizabal C, Pase M, Murabito J, Beiser A, Seshadri S. Grip Strength, Gait Speed and Plasma Markers of Neurodegeneration in Asymptomatic Middle-aged and Older Adults. J Frailty Aging 2022; 11:291-298. [DOI: 10.14283/jfa.2022.17] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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8
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Kalpana K, Rani VA, Seshadri S, Kiran BR. BMIM[BF4]: An Efficient Ionic Liquid Medium for the Synthesis of Chromeno[b]pyridines as Potential Anticancer Agents. Russ J Org Chem 2021. [DOI: 10.1134/s1070428021090177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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9
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Merrett C, Schlager D, Yasmin E, Seshadri S, Serhal P, Ralph D, Sangster P. P–128 Audit of testicular sperm in assisted conception for non-azoospermic infertile couples. Hum Reprod 2021. [DOI: 10.1093/humrep/deab130.127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Study question
What live birth rate do we see when we use testicular sperm in ART for non-azoospermic couples after at least one previous failed cycle?
Summary answer
In our cohort of couples 24% had a live birth using testicular sperm and therefore was not higher than national average ART rates.
What is known already
There is increased interest in using testicular sperm in assisted reproduction technology (ART) to improve outcomes after previous failed cycles. Mehta et al. reported results of a 50% live birth rate using testicular sperm in the first cycle for couples with oligospermia and a history of failed cycles with ejaculated sperm. We aim to audit our results in a similar population of couples.
Study design, size, duration
St Peters Andrology Centre in London, United Kingdom completed 128 surgical testicular sperm retrievals reviewed between the two-year period of 2018–2019. We conducted a retrospective audit of their paper-based records to identify those couples with injectable sperm on their semen analysis and who had previous cycles attempts using ejaculated sperm.
Participants/materials, setting, methods
We identified 27 couples who underwent testicular sperm extraction despite having an ejaculated semen analysis with injectable sperm and at least one previous failed cycle. A systematic review of their paper and electronic medical record was conducted to assess live birth rates and fertilization rates from ART.
Main results and the role of chance
Couples had an average male age of 41 (range 31–60) and an average female age of 38 (range 30–45). The men had an average serum testosterone of 15 nmol/L (range 8–35 nmol/L) and an average serum FSH of 8.9 IU/L (range 1.7–30 IU/L). 59% (n = 17) of men had a DNA fragmentation index completed with an average score of 41% (range 31%–51[Y1]%). In the women the mean serum anti-Müllerian hormone (AMH) was 15.8 pmol/l (range 1–64 pmol/l). With ejaculated sperm the fertilization rate was 59% (95% CI [27%, 59%]) and blastocyst conversion rate was 43% (95% CI [50%, 69%]). There was no statistical significance with testicular sperm where the fertilization rate was 58% (95% CI [51%, 65%]) and blastocyst conversion rate was 54% (95% CI [40%, 67%]). Overall, there were 7 clinical pregnancies in this population of couples. Of these clinical pregnancies, 2 miscarried and 5 progressed to a live birth. This audit yielded a live birth rate per cycle of 15% and a live birth rate per couple of 24%.
Limitations, reasons for caution
Limitations of the study are low number of patients and absence of a control group.
Wider implications of the findings: We recommend caution and further analysis going forward using testicular sperm in ART where ejaculated sperm in available.
Trial registration number
Not applicable
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Affiliation(s)
- C Merrett
- University College London Hospital, Andrology, London, United Kingdom
| | - D Schlager
- University of Freiburg, Department of Urology, Hugstetter, Germany
| | - E Yasmin
- University College London Hospital, Reproductive Medicine, London, United Kingdom
| | - S Seshadri
- The Centre for Reproductive & Genetic Health, Reproductive Medicine, London, United Kingdom
| | - P Serhal
- University College London Hospital, Reproductive Medicine, London, United Kingdom
| | - D Ralph
- University College London Hospital, Andrology, London, United Kingdom
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Cardenas Armas D, Duran-Retamal M, Odia R, Cawood S, Drew E, Yasmin E, Saab W, Serhal P, Seshadri S. O-093 Male translocations in recurrent pregnancy loss: Natural conception versus PGD treatment: what is the right option?: A systematic review and meta-analysis. Hum Reprod 2021. [DOI: 10.1093/humrep/deab125.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Study question
Does PGD treatment in couples with a history of RPL due to male translocations improve the outcome, increasing LBR and reducing miscarriage rate and time taken to live birth?
Summary answer
Live birth rate is significantly increased, miscarriage rate is significantly reduced using PGD. Time taken to achieve live birth rate is shorter in PGD treatment.
What is known already
Reciprocal translocation are the most common structural rearrangement in infertile men. The specific chromosomes and breakpoints involved might play an important role, often expressed as abnormal semen parameters or repeated pregnancy loss (RPL). The genetic counselling of these men remains challenging. Previous studies and meta-analysis performed showed no difference in live birth rate when comparing natural conception versus PGD treatment. However, the difference in miscarriage rate and time to live birth between PGD and natural conception has not been reported before in the medical literature.
Study design, size, duration
A systematic review of the literature was conducted through MEDLINE, EMBASE, and the Cochrane database up until December 2020. A comprehensive search yield 287 articles, 25 of which were included for abstract reading, finally, six were included in the meta-analysis.
Participants/materials, setting, methods
The six selected articles, reported on Live birth rate (LBR), miscarriage rate and time to live birth (TTLB) for natural conception compared to PGD for the same cohort of patients. All of the included articles were of retrospective design. The primary outcome was the comparison in LBR and the second outcome was the analysis in miscarriage rate and TTLB in the PGD group versus natural conception.
Main results and the role of chance
A total of 1438 couples that conceived naturally, had a LBR of 22.46%, compared with 43,17% among 681 couples that underwent PGD (0.53 95% CI (0.43-0.65) p o < 0,00001). The six articles included in this meta-analysis had significant homogeneity (I2 = 96%). Comparison of miscarriage rates, natural conception represented 1339 miscarriages out of 1836 pregnancies, in comparison with 44 miscarriages out of 558 pregnancies achieved through PGD. The OR showed a 10 fold increase risk of miscarriage when conceiving naturally in couples with a male translocation (10.18; 95% CI (2.88-36.04) p = 0.0003).
Regarding TTLB, the difference was not statistically significant, however it did reflect that PGD patients will have a shorter TTLB (3.56 95% CI (-0.88-8.00)p = 0.12). One of the studies included, took into account the waiting list to access PGD funding, prolonging therefore the TTLB in the PGD group.
Limitations, reasons for caution
The main limitation of this study is the low number of studies. TTLB should be interpreted with caution given that one of the articles included the time of the waiting lists. More studies could demonstrate a shorter time period for these couples to conceive and have a successful ongoing pregnancy.
Wider implications of the findings
First study to demonstrate the value of PGD in decreasing miscarriage rates in couples with RPL. Specially when counselling couples with history of RPL with male translocations. PGD should be offered in these couples to improve the outcome, and to diminish the physical, emotional and sequelae of RPL and TOP.
Trial registration number
not applicable
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Affiliation(s)
- D Cardenas Armas
- The Centre for Reproductive and Genetic Health, The Centre for Reproductive and Genetic Health, London, United Kingdom
| | - M Duran-Retamal
- The Centre for Reproductive and Genetic Health, The Centre for Reproductive and Genetic Health, London, United Kingdom
| | - R Odia
- The Centre for Reproductive and Genetic Health, The Centre for Reproductive and Genetic Health, London, United Kingdom
| | - S Cawood
- The Centre for Reproductive and Genetic Health, The Centre for Reproductive and Genetic Health, London, United Kingdom
| | - E Drew
- The Centre for Reproductive and Genetic Health, The Centre for Reproductive and Genetic Health, London, United Kingdom
| | - E Yasmin
- University College Hospital UCLH, Reproductive Medicine, London, United Kingdom
| | - W Saab
- The Centre for Reproductive and Genetic Health, The Centre for Reproductive and Genetic Health, London, United Kingdom
| | - P Serhal
- The Centre for Reproductive and Genetic Health, The Centre for Reproductive and Genetic Health, London, United Kingdom
| | - S Seshadri
- The Centre for Reproductive and Genetic Health, The Centre for Reproductive and Genetic Health, London, United Kingdom
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11
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Merrett C, Schlager D, Yasmin E, Seshadri S, Serhal P, Ralph D, Sangster P. Audit of testicular sperm in assisted conception for non-azoospermic infertile couples. Eur Urol 2021. [DOI: 10.1016/s0302-2838(21)00891-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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12
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Tamhane T, Baliga P, Chidambarathanu S, Suresh I, Seshadri S. Echogenic Fetal Heart Without Conduction Defect in Maternal Autoimmune Disease: A Lesser Known Association. J Fetal Med 2021. [DOI: 10.1007/s40556-021-00299-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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13
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Kumaravelan S, Seshadri S, Suresh R, Ravichandran K, Sathishkumar P, Shanthaseelan K, Suganthi N. Effect of Zn dopant on SnO2 nano-pyramids for photocatalytic degradation. Chem Phys Lett 2021. [DOI: 10.1016/j.cplett.2021.138352] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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14
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Mahalingam HV, Rangasami R, Seshadri S, Suresh I. Imaging spectrum of posterior fossa anomalies on foetal magnetic resonance imaging with an algorithmic approach to diagnosis. Pol J Radiol 2021; 86:e183-e194. [PMID: 33828631 PMCID: PMC8018271 DOI: 10.5114/pjr.2021.105014] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Accepted: 04/30/2020] [Indexed: 11/17/2022] Open
Abstract
Posterior fossa abnormalities are one of the most common indications for performing foetal magnetic resonance imaging (FMRI). Ultrasonography is the initial imaging modality for assessment of foetal posterior fossa. Abnormal findings on ultrasonography warrant further evaluation with FMRI because it offers excellent soft-tissue contrast resolution and multiplanar capabilities. The neurological prognosis of different posterior fossa anomalies varies widely. FMRI plays a crucial role in confirming the diagnosis, assessing the prognosis, and counselling patients regarding continuation of pregnancy and possible post-natal developmental outcome. In this review we present the imaging spectrum of posterior fossa anomalies that readers can encounter in practice, highlight salient points in favour of each diagnosis, and provide a simplified algorithmic approach to reach the final diagnosis.
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Affiliation(s)
- Harsha Vardhan Mahalingam
- Department of Radiology, Sri Ramachandra Medical College and Research Institute (SRMC & RI), Chennai, India
| | - Rajeswaran Rangasami
- Department of Radiology, Sri Ramachandra Medical College and Research Institute (SRMC & RI), Chennai, India
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15
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Sabu B, Raja V, Srinivasan L, Suresh I, Seshadri S. Prenatal Diagnosis of Agnathia/Otocephaly: Associations and Outcomes-Large Case Series and Review of Literature. J Fetal Med 2021. [DOI: 10.1007/s40556-020-00284-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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16
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Velayudhan A, Seshadri S, Jagadeesan S, Saravanan J, Yadav R, Yeung LF. Evaluation of a hospital-based surveillance system for birth defects in Chennai, India. Int J Community Med Public Health 2021; 8:5484-5488. [PMID: 38617822 PMCID: PMC11010458 DOI: 10.18203/2394-6040.ijcmph20214293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
The Birth Defects Registry of India-Chennai (BDRI-C) was created in 2001 to monitor birth defects and provide timely referrals. Using established guidelines to evaluate surveillance systems, we examined the following attributes of BDRI-C to help strengthen the registry: simplicity, flexibility, data quality, representativeness, acceptability, timeliness, and stability. We reviewed BDRI-C documents, including reporting forms; interviewed key informants; and calculated data completeness, coverage, and reporting time. BDRI-C captured 14% of the births in Chennai April 2013 - March 2014. About 7% of institutions in Chennai registered in BDRI-C, and of those registered, 37% provided data in 2013. Median reporting time was 44 days after birth in 2013. BDRI-C is a useful, simple, flexible, and timely passive birth defects surveillance system; however, improvements can be made to ensure BDRI-C is representative of Chennai, data processing and quality checks are on-going, and the system is acceptable for member institutions and stable.
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Affiliation(s)
- Anoop Velayudhan
- Epidemic Intelligence Service India Programme-National Centre for Disease Control, New Delhi, India
| | | | | | | | | | - Lorraine F. Yeung
- National Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
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Yadav RM, Gupta M, Dalvi A, Bargir UA, Hule G, Shabrish S, Aluri J, Kulkarni M, Kambli P, Uppuluri R, Seshadri S, Jagadeesh S, Suresh B, Raja J, Taur P, Malaischamy S, Ghosh P, Mahalingam S, Kadam P, Lashkari HP, Tamhankar P, Tamhankar V, Mithbawkar S, Bhattad S, Jhawar P, Makam A, Bansal V, Prasad M, Govindaraj G, Guhan B, Bharadwaj Tallapaka K, Desai M, Raj R, Madkaikar MR. Prenatal Diagnosis for Primary Immunodeficiency Disorders-An Overview of the Indian Scenario. Front Immunol 2020; 11:612316. [PMID: 33365035 PMCID: PMC7750517 DOI: 10.3389/fimmu.2020.612316] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 11/04/2020] [Indexed: 01/13/2023] Open
Abstract
Prenatal Diagnosis (PND) forms an important part of primary preventive management for families having a child affected with primary immunodeficiency. Although individually sparse, collectively this group of genetic disorders represents a significant burden of disease. This paper discusses the prenatal services available for affected families at various centers across the country and the challenges and ethical considerations associated with genetic counseling. Mutation detection in the index case and analysis of chorionic villous sampling or amniocentesis remain the preferred procedures for PND and phenotypic analysis of cordocentesis sample is reserved for families with well-characterized index case seeking PND in the latter part of the second trimester of pregnancy. A total of 112 families were provided PND services in the last decade and the presence of an affected fetus was confirmed in 32 families. Post-test genetic counseling enabled the affected families to make an informed decision about the current pregnancy.
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Affiliation(s)
- Reetika Malik Yadav
- Center of Excellence for PIDs, Department of Pediatric Immunology and Leucocyte Biology, ICMR-National Institute of Immunohaematology, Mumbai, India
| | - Maya Gupta
- Center of Excellence for PIDs, Department of Pediatric Immunology and Leucocyte Biology, ICMR-National Institute of Immunohaematology, Mumbai, India
| | - Aparna Dalvi
- Center of Excellence for PIDs, Department of Pediatric Immunology and Leucocyte Biology, ICMR-National Institute of Immunohaematology, Mumbai, India
| | - Umair Ahmed Bargir
- Center of Excellence for PIDs, Department of Pediatric Immunology and Leucocyte Biology, ICMR-National Institute of Immunohaematology, Mumbai, India
| | - Gouri Hule
- Center of Excellence for PIDs, Department of Pediatric Immunology and Leucocyte Biology, ICMR-National Institute of Immunohaematology, Mumbai, India
| | - Snehal Shabrish
- Center of Excellence for PIDs, Department of Pediatric Immunology and Leucocyte Biology, ICMR-National Institute of Immunohaematology, Mumbai, India
| | - Jahnavi Aluri
- Center of Excellence for PIDs, Department of Pediatric Immunology and Leucocyte Biology, ICMR-National Institute of Immunohaematology, Mumbai, India
| | - Manasi Kulkarni
- Center of Excellence for PIDs, Department of Pediatric Immunology and Leucocyte Biology, ICMR-National Institute of Immunohaematology, Mumbai, India
| | - Priyanka Kambli
- Center of Excellence for PIDs, Department of Pediatric Immunology and Leucocyte Biology, ICMR-National Institute of Immunohaematology, Mumbai, India
| | - Ramya Uppuluri
- Department of Pediatric Hematology-Oncology, Blood Marrow Transplantation, Apollo Hospitals, Chennai, India
| | - Suresh Seshadri
- Department of Clinical Genetics & Genetic Counseling, Mediscan Systems, Chennai, India
| | - Sujatha Jagadeesh
- Department of Clinical Genetics & Genetic Counseling, Mediscan Systems, Chennai, India
| | - Beena Suresh
- Department of Clinical Genetics & Genetic Counseling, Mediscan Systems, Chennai, India
| | - Jayarekha Raja
- Department of Clinical Genetics & Genetic Counseling, Mediscan Systems, Chennai, India
| | - Prasad Taur
- Department of Immunology and Department of Pediatric Hemato-Oncology, Bai Jerbai Wadia Hospital for Children, Mumbai, India
| | | | | | | | - Priya Kadam
- MedGenome Labs Private Limited, Bangalore, India
| | - Harsha Prasada Lashkari
- Department of Pediatrics, Kasturba Medical College Hospital, Manipal Academy of Higher Education, Mangalore, India
| | | | | | | | - Sagar Bhattad
- Division of Pediatric Immunology and Rheumatology, Department of Pediatrics, Aster CMI Hospital, Bangalore, India
| | - Prerna Jhawar
- Department of Fetal Medicine, Motherhood Hospital, Bangalore, India
| | - Adinarayan Makam
- Department of Fetal Medicine, Adi Advanced Centre for Fetal Care, Bangalore, India
| | - Vandana Bansal
- Fetal Medicine Department Surya Hospitals, Mumbai, India
| | | | - Geeta Govindaraj
- Department of Pediatrics, Government Medical College, Kozhikode, Calicut, India
| | - Beena Guhan
- Department of Pediatrics, Government Medical College, Kozhikode, Calicut, India
| | | | - Mukesh Desai
- Department of Immunology and Department of Pediatric Hemato-Oncology, Bai Jerbai Wadia Hospital for Children, Mumbai, India
| | - Revathi Raj
- Department of Pediatric Hematology-Oncology, Blood Marrow Transplantation, Apollo Hospitals, Chennai, India
| | - Manisha Rajan Madkaikar
- Center of Excellence for PIDs, Department of Pediatric Immunology and Leucocyte Biology, ICMR-National Institute of Immunohaematology, Mumbai, India
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Seshadri S, Morris G, Serhal P, Saab W. Assisted conception in women of advanced maternal age. Best Pract Res Clin Obstet Gynaecol 2020; 70:10-20. [PMID: 32921559 DOI: 10.1016/j.bpobgyn.2020.06.012] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Accepted: 06/14/2020] [Indexed: 11/18/2022]
Abstract
A delay in childbearing to later in life has increased the number of women of advanced maternal age (AMA) opting for assisted reproduction. Women should be made aware that there are age-related changes to fertility, including a decline in oocyte reserve and quality, in addition to an increase in the number of oocyte chromosomal aberrations. Success rates of assisted reproductive technology (ART) cycles decrease with advanced maternal age. There are different fertility options for women of AMA, including fertility preservation (oocyte or embryo freezing), in vitro fertilisation (IVF treatment) with or without preimplantation genetic screening and oocyte or embryo donation. Detailed counselling needs to be offered to these women with regard to the risks, success rates, ethical and legal implications of these fertility treatment options. Women of AMA should be screened for underlying medical conditions that could have an impact on maternal and neonatal morbidity and mortality.
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Affiliation(s)
- S Seshadri
- The Centre for Reproductive and Genetic Health (CRGH), London, UK.
| | - G Morris
- St Michael's Hospital, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
| | - P Serhal
- The Centre for Reproductive and Genetic Health (CRGH), London, UK
| | - W Saab
- The Centre for Reproductive and Genetic Health (CRGH), London, UK
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19
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Chaemsaithong P, Sahota D, Pooh RK, Zheng M, Ma R, Chaiyasit N, Koide K, Shaw SW, Seshadri S, Choolani M, Panchalee T, Yapan P, Sim WS, Sekizawa A, Hu Y, Shiozaki A, Saito S, Leung TY, Poon LC. First-trimester pre-eclampsia biomarker profiles in Asian population: multicenter cohort study. Ultrasound Obstet Gynecol 2020; 56:206-214. [PMID: 31671479 DOI: 10.1002/uog.21905] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Revised: 10/08/2019] [Accepted: 10/11/2019] [Indexed: 06/10/2023]
Abstract
OBJECTIVES To (i) evaluate the applicability of the European-derived biomarker multiples of the median (MoM) formulae for risk assessment of preterm pre-eclampsia (PE) in seven Asian populations, spanning the east, southeast and south regions of the continent, (ii) perform quality-assurance (QA) assessment of the biomarker measurements and (iii) establish criteria for prospective ongoing QA assessment of biomarker measurements. METHODS This was a prospective, non-intervention, multicenter study in 4023 singleton pregnancies, at 11 to 13 + 6 weeks' gestation, in 11 recruiting centers in China, Hong Kong, India, Japan, Singapore, Taiwan and Thailand. Women were screened for preterm PE between December 2016 and June 2018 and gave written informed consent to participate in the study. Maternal and pregnancy characteristics were recorded and mean arterial pressure (MAP), mean uterine artery pulsatility index (UtA-PI) and maternal serum placental growth factor (PlGF) were measured in accordance with The Fetal Medicine Foundation (FMF) standardized measurement protocols. MAP, UtA-PI and PlGF were transformed into MoMs using the published FMF formulae, derived from a largely Caucasian population in Europe, which adjust for gestational age and covariates that affect directly the biomarker levels. Variations in biomarker MoM values and their dispersion (SD) and cumulative sum tests over time were evaluated in order to identify systematic deviations in biomarker measurements from the expected distributions. RESULTS In the total screened population, the median (95% CI) MoM values of MAP, UtA-PI and PlGF were 0.961 (0.956-0.965), 1.018 (0.996-1.030) and 0.891 (0.861-0.909), respectively. Women in this largely Asian cohort had approximately 4% and 11% lower MAP and PlGF MoM levels, respectively, compared with those expected from normal median formulae, based on a largely Caucasian population, whilst UtA-PI MoM values were similar. UtA-PI and PlGF MoMs were beyond the 0.4 to 2.5 MoM range (truncation limits) in 16 (0.4%) and 256 (6.4%) pregnancies, respectively. QA assessment tools indicated that women in all centers had consistently lower MAP MoM values than expected, but were within 10% of the expected value. UtA-PI MoM values were within 10% of the expected value at all sites except one. Most PlGF MoM values were systematically 10% lower than the expected value, except for those derived from a South Asian population, which were 37% higher. CONCLUSIONS Owing to the anthropometric differences in Asian compared with Caucasian women, significant differences in biomarker MoM values for PE screening, particularly MAP and PlGF MoMs, were noted in Asian populations compared with the expected values based on European-derived formulae. If reliable and consistent patient-specific risks for preterm PE are to be reported, adjustment for additional factors or development of Asian-specific formulae for the calculation of biomarker MoMs is required. We have also demonstrated the importance and need for regular quality assessment of biomarker values. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.
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Affiliation(s)
- P Chaemsaithong
- Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong SAR
| | - D Sahota
- Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong SAR
| | - R K Pooh
- CRIFM Clinical Research Institute of Fetal Medicine PMC, Osaka, Japan
| | - M Zheng
- Nanjing Drum Tower Hospital, Nanjing, China
| | - R Ma
- First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - N Chaiyasit
- King Chulalongkorn Memorial Hospital, Bangkok, Thailand
| | - K Koide
- Showa University Hospital, Tokyo, Japan
| | - S W Shaw
- Taipei Chang Gung Memorial Hospital, Taipei, Taiwan
| | | | | | | | - P Yapan
- Siriraj Hospital, Bangkok, Thailand
| | - W S Sim
- KK Women's and Children's Hospital, Singapore
| | | | - Y Hu
- Nanjing Drum Tower Hospital, Nanjing, China
| | - A Shiozaki
- University of Toyama University Hospital, Toyama, Japan
| | - S Saito
- University of Toyama University Hospital, Toyama, Japan
| | - T Y Leung
- Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong SAR
| | - L C Poon
- Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong SAR
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Baril A, Beiser AS, Redline S, McGrath ER, Aparicio HJ, Gottlieb DJ, Seshadri S, Himali JJ, Pase MP. 0419 IL-6 Moderates the Association Between Obstructive Sleep Apnea Severity and Incident Alzheimer’s Disease: The Framingham Heart Study. Sleep 2020. [DOI: 10.1093/sleep/zsaa056.416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Introduction
Both sleep disturbances and inflammation are potential risk factors for Alzheimer’s disease (AD). However, it is unknown how inflammation and sleep interact together to influence the risk of developing AD dementia. Our objective was to evaluate whether interleukin-6 (IL-6) levels interact with sleep disturbances when predicting incident clinical AD.
Methods
We studied participants in the Framingham Heart Study Offspring cohort who completed in-home overnight polysomnography. Sleep characteristics were continuous and included sleep duration, wake after sleep onset (WASO), and apnea-hypopnea index (AHI). Participants were stratified into quartiles of IL-6 levels. Surveillance for incident AD dementia occurred over a mean follow-up of 13.4±5.4 years. Using Cox proportional hazards regression models, we tested the interaction of sleep measures by IL-6 quartiles on incident AD dementia. All analyses adjusted for age and sex and P<0.05 was considered significant.
Results
The final sample included 291 dementia-free participants at baseline (age 67.5±4.9 years, 51.6% men). Approximately one quarter of participants had obstructive sleep apnea (OSA; AHI>15) at baseline (median:6.2, Q1:2,3, Q3:14.3). We observed 33 cases of incident AD dementia during follow-up. Although no interaction was observed for either sleep duration or WASO with IL-6 levels, there was a significant interaction of AHI with IL-6 in predicting AD dementia (p=0.002). In the lowest IL-6 quartile, higher AHI was associated with an elevated risk of AD dementia (hazard ratio, 4.15 [95%CI, 1.42, 12.1], p=0.01) whereas no association between AHI and incident AD was observed in other IL-6 quartiles.
Conclusion
Our findings suggest that the pro-inflammatory cytokine IL-6 moderates the association between OSA and incident AD risk. The association between increasing OSA severity and incident AD was only observed in those with lower IL-6 levels, suggesting that this association might be especially apparent when no other confounding risk factors such as inflammation are present.
Support
The Framingham Heart Study is supported by contracts from the National Heart, Lung and Blood Institute, grants from the National Institute on Aging, and grants from the National Institute of Neurological Disorders and Stroke.
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Affiliation(s)
- A Baril
- The Framingham Heart Study, Boston University School of Medicine, Boston, MA
| | - A S Beiser
- The Framingham Heart Study, Boston University School of Medicine, Boston, MA
| | - S Redline
- Brigham & Women’s Hospital, Harvard Medical School, Boston, MA
| | | | - H J Aparicio
- The Framingham Heart Study, Boston University School of Medicine, Boston, MA
| | | | - S Seshadri
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX
| | - J J Himali
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX
| | - M P Pase
- The University of Melbourne, Melbourne, AUSTRALIA
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Seshadri S, Shinde RR, Ram U. Intrafetal laser for midtrimester TRAP sequence-experience from a single center. Prenat Diagn 2020; 40:885-891. [PMID: 32281112 DOI: 10.1002/pd.5707] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2017] [Revised: 12/16/2018] [Accepted: 04/06/2020] [Indexed: 02/01/2023]
Abstract
OBJECTIVE To report our experience and evaluate outcomes in monochorionic pregnancies with Twin Reversed Arterial Perfusion sequence with intrafetal laser therapy. METHODS Retrospective review of records of all pregnancies with TRAP sequence treated by intrafetal laser therapy between 2011 January and 2015 December that were retrieved and analysed. RESULTS Electronic search of the scan database retrieved 57 cases of TRAP sequence during the study period, 7 triplets and 50 monochorionic twins. Intrafetal laser was done in 27 cases, 22 cases of twins and 5 cases of triplets. In the twins group, median gestational age at intervention was 22.5 weeks, the earliest done at 16.3 weeks. The median gestational age at delivery and birth weight was 37 weeks and 2.5 Kgs. The median procedure and delivery interval was 14 weeks. Live birth rate was 17/22 (77%) the pump survival rate was 16/22 (73%). Pregnancies with non-surviving pump were 5 in numbers (5/22). A repeat procedure was warranted in one case. In the triplet group, median gestational age at intervention, delivery and procedure delivery interval was 18, 35 and 17 weeks. CONCLUSION Intrafetal laser is simple, effective and the treatment of choice to interrupt the vascular supply to acardiac twin.
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Affiliation(s)
| | - Roopa R Shinde
- Fetal Medicine Department, Mediscan Systems, Chennai, India
| | - Uma Ram
- Obstetrics and Gynecology, Seethapathy Clinic & Hospital, Chennai, India
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Joseph J, Kiran R, Nabeel PM, Shah MI, Bhaskar A, Ganesh C, Seshadri S, Sivaprakasam M. ARTSENS ® Pen-portable easy-to-use device for carotid stiffness measurement: technology validation and clinical-utility assessment. Biomed Phys Eng Express 2020; 6:025013. [PMID: 33438639 DOI: 10.1088/2057-1976/ab74ff] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
OBJECTIVE The conventional medical imaging modalities used for arterial stiffness measurement are non-scalable and unviable for field-level vascular screening. The need for an affordable, easy-to-operate automated non-invasive technologies remains unmet. To address this need, we present a portable image-free ultrasound device-ARTSENS® Pen, that uses a single-element ultrasound transducer for carotid stiffness evaluation. APPROACH The performance of the device was clinically validated on a cohort of 523 subjects. A clinical-grade B-mode ultrasound imaging system (ALOKA eTracking) was used as the reference. Carotid stiffness measurements were taken using the ARTSENS® Pen in sitting posture emulating field scenarios. MAIN RESULTS A statistically significant correlation (r > 0.80, p < 0.0001) with a non-significant bias was observed between the measurements obtained from the two devices. The ARTSENS® Pen device could perform highly repeatable measurements (with variation smaller than 10%) on a relatively larger percentage of the population when compared to the ALOKA system. The study results also revealed the sensitivity of ARTSENS® Pen to detect changes in arterial stiffness with age. SIGNIFICANCE The easy-to-use technology and the automated algorithms of the ARTSENS® Pen make it suitable for cardiovascular risk assessment in resource-constrained settings.
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Affiliation(s)
- Jayaraj Joseph
- Healthcare Technology Innovation Centre, Indian Institute of Technology Madras, Taramani, Chennai, Tamil Nadu-600 113, India
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Chaemsaithong P, Pooh RK, Zheng M, Ma R, Chaiyasit N, Tokunaka M, Shaw SW, Seshadri S, Choolani M, Wataganara T, Yeo GSH, Wright A, Leung WC, Sekizawa A, Hu Y, Naruse K, Saito S, Sahota D, Leung TY, Poon LC. Prospective evaluation of screening performance of first-trimester prediction models for preterm preeclampsia in an Asian population. Am J Obstet Gynecol 2019; 221:650.e1-650.e16. [PMID: 31589866 DOI: 10.1016/j.ajog.2019.09.041] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Revised: 09/22/2019] [Accepted: 09/25/2019] [Indexed: 12/17/2022]
Abstract
BACKGROUND The administration of aspirin <16 weeks gestation to women who are at high risk for preeclampsia has been shown to reduce the rate of preterm preeclampsia by 65%. The traditional approach to identify such women who are at risk is based on risk factors from maternal characteristics, obstetrics, and medical history as recommended by the American College of Obstetricians and Gynecologists and the National Institute for Health and Care Excellence. An alternative approach to screening for preeclampsia has been developed by the Fetal Medicine Foundation. This approach allows the estimation of patient-specific risks of preeclampsia that requires delivery before a specified gestational age with the use of Bayes theorem-based model. OBJECTIVE The purpose of this study was to examine the diagnostic accuracy of the Fetal Medicine Foundation Bayes theorem-based model, the American College of Obstetricians and Gynecologists, and the National Institute for Health and Care Excellence recommendations for the prediction of preterm preeclampsia at 11-13+6 weeks gestation in a large Asian population STUDY DESIGN: This was a prospective, nonintervention, multicenter study in 10,935 singleton pregnancies at 11-13+6 weeks gestation in 11 recruiting centers across 7 regions in Asia between December 2016 and June 2018. Maternal characteristics and medical, obstetric, and drug history were recorded. Mean arterial pressure and uterine artery pulsatility indices were measured according to standardized protocols. Maternal serum placental growth factor concentrations were measured by automated analyzers. The measured values of mean arterial pressure, uterine artery pulsatility index, and placental growth factor were converted into multiples of the median. The Fetal Medicine Foundation Bayes theorem-based model was used for the calculation of patient-specific risk of preeclampsia at <37 weeks gestation (preterm preeclampsia) and at any gestation (all preeclampsia) in each participant. The performance of screening for preterm preeclampsia and all preeclampsia by a combination of maternal factors, mean arterial pressure, uterine artery pulsatility index, and placental growth factor (triple test) was evaluated with the adjustment of aspirin use. We examined the predictive performance of the model by the use of receiver operating characteristic curve and calibration by measurements of calibration slope and calibration in the large. The detection rate of screening by the Fetal Medicine Foundation Bayes theorem-based model was compared with the model that was derived from the application of American College of Obstetricians and Gynecologists and National Institute for Health and Care Excellence recommendations. RESULTS There were 224 women (2.05%) who experienced preeclampsia, which included 73 cases (0.67%) of preterm preeclampsia. In pregnancies with preterm preeclampsia, the mean multiples of the median values of mean arterial pressure and uterine artery pulsatility index were significantly higher (mean arterial pressure, 1.099 vs 1.008 [P<.001]; uterine artery pulsatility index, 1.188 vs 1.063[P=.006]), and the mean placental growth factor multiples of the median was significantly lower (0.760 vs 1.100 [P<.001]) than in women without preeclampsia. The Fetal Medicine Foundation triple test achieved detection rates of 48.2%, 64.0%, 71.8%, and 75.8% at 5%, 10%, 15%, and 20% fixed false-positive rates, respectively, for the prediction of preterm preeclampsia. These were comparable with those of previously published data from the Fetal Medicine Foundation study. Screening that used the American College of Obstetricians and Gynecologists recommendations achieved detection rate of 54.6% at 20.4% false-positive rate. The detection rate with the use of National Institute for Health and Care Excellence guideline was 26.3% at 5.5% false-positive rate. CONCLUSION Based on a large number of women, this study has demonstrated that the Fetal Medicine Foundation Bayes theorem-based model is effective in the prediction of preterm preeclampsia in an Asian population and that this method of screening is superior to the approach recommended by American College of Obstetricians and Gynecologists and the National Institute for Health and Care Excellence. We have also shown that the Fetal Medicine Foundation prediction model can be implemented as part of routine prenatal care through the use of the existing infrastructure of routine prenatal care.
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Affiliation(s)
| | - Ritsuko K Pooh
- CRIFM Clinical Research Institute of Fetal Medicine, Osaka, Japan
| | | | - Runmei Ma
- First Affiliated Hospital of Kunming Medical University, Kunming, China
| | | | | | | | | | | | | | | | | | | | | | - Yali Hu
- Nanjing Drum Tower Hospital, Nanjing, China
| | | | - Shigeru Saito
- University of Toyama University Hospital, Toyama, Japan
| | - Daljit Sahota
- Chinese University of Hong Kong, Hong Kong SAR, China
| | | | - Liona C Poon
- Chinese University of Hong Kong, Hong Kong SAR, China.
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Viñals Gonzalez X, Odia R, Naja R, Serhal P, Saab W, Seshadri S, Ben-Nagi J. Euploid blastocysts implant irrespective of their morphology after NGS-(PGT-A) testing in advanced maternal age patients. J Assist Reprod Genet 2019; 36:1623-1629. [PMID: 31165389 DOI: 10.1007/s10815-019-01496-9] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Accepted: 05/24/2019] [Indexed: 11/29/2022] Open
Abstract
PURPOSE Does blastocyst morphology following euploid elective single embryo transfer (eSET) after preimplantation genetic testing for aneuploidies (PGT-A) via next generation sequencing impact clinical outcome? METHODS Two hundred ninety-six patients underwent PGT-A. Of 1549 blastocysts, 1410 blastocysts had a conclusive result after PGT-A and were included for analysis. An eSET policy was followed in a frozen embryo replacement cycle. A total of 179 euploid blastocysts were thawed and transferred. Clinical outcomes were categorized in four different embryo quality groups: excellent, good, average and poor. RESULTS Euploidy rate was 19/36 (52.7%, 95% CI 37-68), 199/470 (42.3%, 95% CI 38-47), 156/676 (23.0%, 95% CI 20-26) and 39/228 (17.1%, 95% CI 13-23) in the excellent, good, average and poor quality blastocyst groups, respectively. Fitted logistic regression analysis taking into account the following covariables: female, age, embryo chromosomal status and day of blastocyst development/biopsy showed that morphology was predictive of the comprehensive chromosome screening result (p < 0.05). A logistic regression analysis was also performed on clinical outcomes taking into account the effect of blastocyst morphology and day of blastocyst development/biopsy. None of the parameters were shown to be significant, suggesting morphology and day of blastocyst development/biopsy do not reduce the competence of euploid embryos (p > 0.05). CONCLUSIONS After eSET, implantation rate was 80-86%; live birth rate per embryo transfer was 60-73% and clinical miscarriage rate was found to be < 10% and were not significantly affected by the embryo morphology. Results are concordant with those reported when using aCGH and highlights the competence of poor-quality euploid embryos.
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Affiliation(s)
- X Viñals Gonzalez
- Embryology Department, The Centre For Reproductive and Genetic Health, 230-232 Great Portland St, London, W1W 5QS, UK.
| | - R Odia
- Embryology Department, The Centre For Reproductive and Genetic Health, 230-232 Great Portland St, London, W1W 5QS, UK
| | - R Naja
- IGENOMIX, 40 Occam Road, Guildford, Surrey, GU2 7YG, UK
| | - P Serhal
- Clinical Department, The Centre For Reproductive and Genetic Health, 230-232 Great Portland St, London, W1W 5QS, UK
| | - W Saab
- Clinical Department, The Centre For Reproductive and Genetic Health, 230-232 Great Portland St, London, W1W 5QS, UK
| | - S Seshadri
- Clinical Department, The Centre For Reproductive and Genetic Health, 230-232 Great Portland St, London, W1W 5QS, UK
| | - J Ben-Nagi
- Clinical Department, The Centre For Reproductive and Genetic Health, 230-232 Great Portland St, London, W1W 5QS, UK
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Verma S, Khambhala P, Joshi S, Kothari V, Patel T, Seshadri S. Evaluating the role of dithiolane rich fraction of Ferula asafoetida (apiaceae) for its antiproliferative and apoptotic properties: in vitro studies. Exp Oncol 2019; 41:90-94. [PMID: 31262162 DOI: 10.32471/exp-oncology.2312-8852.vol-41-no-2.12989] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
UNLABELLED Asafoetida resin has been reported for various biological activities but its use has been widely restricted owing to its pungent smell and pool water solubility. AIM In vitro study of the anticancer potential of microwave-extracted essential oil (EO) of Ferula asafoetida. MATERIALS AND METHODS The phytochemical investigation and in vitro cytotoxicity assessment was carried out in two human liver cancer cell lines. The expression of NFKB1, TGFB1, TNF, CASP3 was analyzed by reverse transcription polymerase chain reaction. RESULTS Ferula asafoetida EO contains high concentrations of dithiolane, which possess antiproliferative activity in human liver carcinoma cell lines (HepG2 and SK-Hep1) in a dose-dependent manner. The bioactive compounds in F. asafoetida are capable of induction of apoptosis and altered NF-kB and TGF-β signalling with increase in caspase-3 and TNF-α expression. CONCLUSION Further elucidation of bioactive molecules and underlying mechanisms could lead to potential intervention in liver cancer in animal models. The safety and efficacy as well as the mode of EO action in animal models would be highly crucial.
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Affiliation(s)
- S Verma
- Institute of Science, Nirma University, Ahmedabad 382481, India
| | - P Khambhala
- Institute of Science, Nirma University, Ahmedabad 382481, India
| | - S Joshi
- National Foods - The Hing Research Center, GIDC-Waghodia, Vadodara 391243, India
| | - V Kothari
- Institute of Science, Nirma University, Ahmedabad 382481, India
| | - T Patel
- Institute of Science, Nirma University, Ahmedabad 382481, India
| | - S Seshadri
- Institute of Science, Nirma University, Ahmedabad 382481, India
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Rose R, Venkatesh A, Pietilä S, Jabeen G, Jagadeesh SM, Seshadri S. Utility and performance of bacterial artificial chromosomes-on-beads assays in chromosome analysis of clinical prenatal samples, products of conception and blood samples. J Obstet Gynaecol Res 2019; 45:830-840. [PMID: 30632238 DOI: 10.1111/jog.13920] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2018] [Accepted: 12/16/2018] [Indexed: 11/30/2022]
Abstract
AIM Chromosome analysis of prenatal samples and products of conception (POC) has conventionally been done by karyotyping (KT). Shortcomings of KT like high turnaround time and culture failure led to technology innovations, such as the bacterial artificial chromosomes (BAC)s-on-Beads (BoBs)-based tests, Prenatal BoBs (prenatal samples) and KaryoLite BoBs (POC samples). In the present study, we validated and evaluated the utility of each test on prenatal, POC and blood samples. METHODS Study A (n = 305; 259 prenatal + 46 blood/POC) and Study B (n = 176; 146 POC/chorionic vill + 30 blood/amniotic fluid) samples were analyzed using Prenatal and KaryoLite BoBs kits, respectively. KT, array-based Comparative Genomic Hybridization (arrayCGH) and fluorescence in situ hybridization (FISH) were used for comparison of results. Ability of KaryoLite BoBs to identify ring chromosomes was tested. RESULTS Prenatal BoBs had zero test failure rate and results of all samples were concordant with KT results. Totally four microdeletions were identified by Prenatal BoBs but not by KT. In Study B, all but two POC samples (one triploid and one tetraploid) were concordant with KT and arrayCGH. Partial chromosomal imbalance detection rate was ~64% and KaryoLite BoBs indicated the presence of a ring chromosome in all four cases. The failure rate of KaryoLite BoBs was 3%. CONCLUSION We conclude that Prenatal BoBs (common aneuploidies and nine microdeletions) together with KT constitutes more comprehensive prenatal testing compared to FISH and KT. KaryoLite BoBs for aneuploidies of all chromosomes is highly successful in POC analysis and the ability to indicate presence of ring chromosomes improves its clinical sensitivity. Both tests are robust and could also be used for different specimens.
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Affiliation(s)
- Rajiv Rose
- Molecular Laboratory, PerkinElmer Health Sciences, Ticel BioPark- Phase II, Chennai, India
| | - Aishwarya Venkatesh
- Molecular Laboratory, PerkinElmer Health Sciences, Ticel BioPark- Phase II, Chennai, India
| | - Sanna Pietilä
- Research & Development Laboratory, PerkinElmer, Singapore, Singapore
| | - Gazala Jabeen
- Cytogenetics Laboratory, PerkinElmer Health Sciences, Ticel BioPark-Phase II, Chennai, India
| | - Sujatha M Jagadeesh
- Molecular Laboratory, PerkinElmer Health Sciences, Ticel BioPark- Phase II, Chennai, India.,Cytogenetics Laboratory, PerkinElmer Health Sciences, Ticel BioPark-Phase II, Chennai, India.,Genetics Department, MediScan Systems, Chennai, India
| | - Suresh Seshadri
- Molecular Laboratory, PerkinElmer Health Sciences, Ticel BioPark- Phase II, Chennai, India.,Cytogenetics Laboratory, PerkinElmer Health Sciences, Ticel BioPark-Phase II, Chennai, India.,Prenatal Diagnosis and Therapy Center, MediScan Systems, Chennai, India
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Colaco SM, Chidambarathanu S, Raja V, Murlidhar L, Jagadeesh S, Suresh I, Seshadri S. Idiopathic Arterial Calcification: Experience from a Single Center in South India. J Fetal Med 2018. [DOI: 10.1007/s40556-018-0176-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/16/2022]
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Ravichandran P, Sugumaran P, Seshadri S, Basta AH. Optimizing the route for production of activated carbon from Casuarina equisetifolia fruit waste. R Soc Open Sci 2018; 5:171578. [PMID: 30109042 PMCID: PMC6083678 DOI: 10.1098/rsos.171578] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2017] [Accepted: 06/07/2018] [Indexed: 05/06/2023]
Abstract
This work deals with optimizing the conditions of pyrolysis and type of activator to upgrade the use of Casuarina equisetifolia fruit waste (CFW) as available and a potential precursor, in production of activated carbon (AC). In this respect, the route of activation was carried out through one- and two-step pyrolysis processes, using different chemical activating agents, such as H3PO4, KOH and ZnCl2. The performance of the CFW-based ACs is assessed by estimating the physico-chemical characteristics (pH, electrical conductivity, bulk density and hardness), surface morphology and scanning electron microscopy, together with carbon yield, surface area and adsorption performance of pollutants in aqueous medium (methylene blue, iodine and molasses colour removal efficiencies). The results show that the two-step activation process was more effective than one-step activation for providing high adsorption performance CFW-based ACs. The maximum Brunauer-Emmett-Teller surface area 547.89 m2 g-1 was produced by using H3PO4 activating agents, and applied two-step pyrolysis. According to the American Water Work Association and based on bulk density of the investigated ACs, we recommend that most of produced ACs are suitable for treating waste water.
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Affiliation(s)
- P. Ravichandran
- Shri AMM Murugappa Chettiar Research Centre (MCRC), Taramani, Chennai 600 113, Tamil Nadu, India
- Authors for correspondence: P. Ravichandran E-mail:
| | - P. Sugumaran
- Shri AMM Murugappa Chettiar Research Centre (MCRC), Taramani, Chennai 600 113, Tamil Nadu, India
| | - S. Seshadri
- Shri AMM Murugappa Chettiar Research Centre (MCRC), Taramani, Chennai 600 113, Tamil Nadu, India
| | - Altaf H. Basta
- National Research Centre, Cellulose and Paper Department, El-Bohousse Street, Dokki 12622, Cairo, Egypt
- Authors for correspondence: Altaf H. Basta e-mail:
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Seshadri S, Saab W, Exeter H, Drew E, Petrie A, Davies M, Serhal P. Clinical outcomes of a vitrified donor oocyte programme: A single UK centre experience. Eur J Obstet Gynecol Reprod Biol 2018; 225:136-140. [PMID: 29709727 DOI: 10.1016/j.ejogrb.2018.04.017] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2018] [Accepted: 04/10/2018] [Indexed: 11/27/2022]
Abstract
OBJECTIVE To assess the survival rate of vitrified oocytes used in an egg recipient programme and compare the clinical outcomes of pregnancy and live-birth rates per warmed oocyte with fresh autologous oocytes. The differences in the obstetrical outcomes between the two groups were also studied. DESIGN A prospective case control study from a single in-vitro fertilisaton (IVF) Centre in UK SETTING: Centre of Reproductive and Genetic Health (CRGH), London POPULATION: Vitrified oocytes from egg donors and autologous fresh oocytes from patients attending for an IVF cycle METHODS: The study group consisted of 1490 vitrified oocytes, which were obtained from 145 egg donors who underwent a stimulation cycle at CRGH Centre. The control group included 145 age-matched women who underwent intra cytoplasmic sperm injection (ICSI) treatment with their own oocytes (n = 1528). The clinical outcomes clinical pregnancy rates (CPR) and live-birth rates (LBR) and obstetrical outcomes (gestational age and weight at delivery) were compared between the two groups. Statistical analysis of the summary data and logistic regression analysis was performed using statistical packages (SPSS Version 23 and Stata 2015). The percentages of all parameters in the cases and control groups were compared by Fisher's exact test. A statistical significance level of 5% was adopted throughout the study. MAIN OUTCOME MEASURES Survival rate per thawed oocyte, clinical pregnancy rate and live-birth rate per embryo transfer was compared to the autologous oocyte group RESULTS: The survival rate of vitrified oocytes was 73.6% (95% CI: 71.3-75.8%). The clinical pregnancy rate (per embryo transfer) using vitrified oocytes was found to be 51.8% compared to 59.3% in the control group. The live birth rate per embryo transfer in the vitrified oocyte group was 46% (95% CI 37.4-54.7%) compared to 57.1% (95% CI 48.5-68.5%) in the control group. The live-birth rate per thawed oocyte was found to be 4.2%. The gestational ages of the fetus at delivery in both the groups were comparable 39.0 (95% CI 32.7-41.9%) and 39.1 (95% CI 25.6-42.0) (p = 0.38). There was no statistically significant difference in the birth weight between the study and the control group 3100 g (750-4337) and 3232 g (1616-4500) respectively (p = 0.28). CONCLUSIONS This is the first study reporting on the efficacy of a vitrified donor oocyte programme from within the UK. There were no significant differences in the obstetrical outcomes between vitrified donor oocytes and autologous oocytes. The above data will be encouraging for women who are undertaking egg freezing for medical and or social reasons.
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Affiliation(s)
- S Seshadri
- The Centre for Reproductive & Genetic Health, 230-232 Great Portland Street, London, W1W 5QS, UK.
| | - W Saab
- The Centre for Reproductive & Genetic Health, 230-232 Great Portland Street, London, W1W 5QS, UK
| | - H Exeter
- The Centre for Reproductive & Genetic Health, 230-232 Great Portland Street, London, W1W 5QS, UK
| | - E Drew
- The Centre for Reproductive & Genetic Health, 230-232 Great Portland Street, London, W1W 5QS, UK
| | - A Petrie
- The Centre for Reproductive & Genetic Health, 230-232 Great Portland Street, London, W1W 5QS, UK; Biostatistics Unit, UCL Eastman Dental Institute, 256 Grays Inn Road, London, UK
| | - M Davies
- Department of Women's Health, University College London Hospitals, London, UK
| | - P Serhal
- The Centre for Reproductive & Genetic Health, 230-232 Great Portland Street, London, W1W 5QS, UK
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Shinde R, James P, Suresh S, Ram U, Seshadri S. Radiofrequency Ablation in Complicated Monochorionic Pregnancy: Initial Experience. J Fetal Med 2018. [DOI: 10.1007/s40556-017-0145-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Olson NC, Raffield LM, Lange LA, Lange EM, Longstreth WT, Chauhan G, Debette S, Seshadri S, Reiner AP, Tracy RP. Associations of activated coagulation factor VII and factor VIIa-antithrombin levels with genome-wide polymorphisms and cardiovascular disease risk. J Thromb Haemost 2018; 16:19-30. [PMID: 29112333 PMCID: PMC5760305 DOI: 10.1111/jth.13899] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2017] [Indexed: 11/26/2022]
Abstract
ESSENTIALS Essentials A fraction of coagulation factor VII circulates in blood as an activated protease (FVIIa). We evaluated FVIIa and FVIIa-antithrombin (FVIIa-AT) levels in the Cardiovascular Health Study. Polymorphisms in the F7 and PROCR loci were associated with FVIIa and FVIIa-AT levels. FVIIa may be an ischemic stroke risk factor in older adults and FVIIa-AT may assess mortality risk. SUMMARY Background A fraction of coagulation factor (F) VII circulates as an active protease (FVIIa). FVIIa also circulates as an inactivated complex with antithrombin (FVIIa-AT). Objective Evaluate associations of FVIIa and FVIIa-AT with genome-wide single nucleotide polymorphisms (SNPs) and incident coronary heart disease, ischemic stroke and mortality. Patients/Methods We measured FVIIa and FVIIa-AT in 3486 Cardiovascular Health Study (CHS) participants. We performed a genome-wide association scan for FVIIa and FVIIa-AT in European-Americans (n = 2410) and examined associations of FVII phenotypes with incident cardiovascular disease. Results In European-Americans, the most significant SNP for FVIIa and FVIIa-AT was rs1755685 in the F7 promoter region on chromosome 13 (FVIIa, β = -25.9 mU mL-1 per minor allele; FVIIa-AT, β = -26.6 pm per minor allele). Phenotypes were also associated with rs867186 located in PROCR on chromosome 20 (FVIIa, β = 7.8 mU mL-1 per minor allele; FVIIa-AT, β = 9.9 per minor allele). Adjusted for risk factors, a one standard deviation higher FVIIa was associated with increased risk of ischemic stroke (hazard ratio [HR], 1.12; 95% confidence interval [CI], 1.01, 1.23). Higher FVIIa-AT was associated with mortality from all causes (HR, 1.08; 95% CI, 1.03, 1.12). Among European-American CHS participants the rs1755685 minor allele was associated with lower ischemic stroke (HR, 0.69; 95% CI, 0.54, 0.88), but this association was not replicated in a larger multi-cohort analysis. Conclusions The results support the importance of the F7 and PROCR loci in variation in circulating FVIIa and FVIIa-AT. The findings suggest FVIIa is a risk factor for ischemic stroke in older adults, whereas higher FVIIa-AT may reflect mortality risk.
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Affiliation(s)
- N C Olson
- Department of Pathology and Laboratory Medicine, Robert Larner, M.D. College of Medicine, University of Vermont, Burlington, VT, USA
- Cardiovascular Research Institute of Vermont, Robert Larner, M.D. College of Medicine, University of Vermont, Burlington, VT, USA
| | - L M Raffield
- Department of Genetics, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - L A Lange
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - E M Lange
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - W T Longstreth
- Department of Neurology, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - G Chauhan
- INSERM U1219 Neuroepidemiology, Bordeaux, France
- University of Bordeaux, Bordeaux, France
- Centre for Brain Research, Indian Institute of Science, Bangalore, India
| | - S Debette
- INSERM U1219 Neuroepidemiology, Bordeaux, France
- University of Bordeaux, Bordeaux, France
- Department of Neurology, Bordeaux University Hospital, Bordeaux, France
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- National Heart, Lung, and Blood Institute Framingham Heart Study, Framingham, MA, USA
| | - S Seshadri
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- National Heart, Lung, and Blood Institute Framingham Heart Study, Framingham, MA, USA
| | - A P Reiner
- Department of Neurology, Bordeaux University Hospital, Bordeaux, France
| | - R P Tracy
- Department of Pathology and Laboratory Medicine, Robert Larner, M.D. College of Medicine, University of Vermont, Burlington, VT, USA
- Cardiovascular Research Institute of Vermont, Robert Larner, M.D. College of Medicine, University of Vermont, Burlington, VT, USA
- Department of Biochemistry, Robert Larner, M.D. College of Medicine, University of Vermont, Burlington, VT, USA
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Beecham GW, Bis JC, Martin ER, Choi SH, DeStefano AL, van Duijn CM, Fornage M, Gabriel SB, Koboldt DC, Larson DE, Naj AC, Psaty BM, Salerno W, Bush WS, Foroud TM, Wijsman E, Farrer LA, Goate A, Haines JL, Pericak-Vance MA, Boerwinkle E, Mayeux R, Seshadri S, Schellenberg G. The Alzheimer's Disease Sequencing Project: Study design and sample selection. Neurol Genet 2017; 3:e194. [PMID: 29184913 PMCID: PMC5646177 DOI: 10.1212/nxg.0000000000000194] [Citation(s) in RCA: 108] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/01/2017] [Accepted: 08/17/2017] [Indexed: 11/25/2022]
Affiliation(s)
- Gary W Beecham
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
| | - J C Bis
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
| | - E R Martin
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
| | - S-H Choi
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
| | - A L DeStefano
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
| | - C M van Duijn
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
| | - M Fornage
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
| | - S B Gabriel
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
| | - D C Koboldt
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
| | - D E Larson
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
| | - A C Naj
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
| | - B M Psaty
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
| | - W Salerno
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
| | - W S Bush
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
| | - T M Foroud
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
| | - E Wijsman
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
| | - L A Farrer
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
| | - A Goate
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
| | - J L Haines
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
| | - Margaret A Pericak-Vance
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
| | - E Boerwinkle
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
| | - R Mayeux
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
| | - S Seshadri
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
| | - G Schellenberg
- John P. Hussman Institute for Human Genomics (G.W.B., E.R.M., M.A.P.-V.) and Dr. John T. Macdonald Foundation Department of Human Genetics (G.W.B., E.R.M., M.A.P.-V.), Miller School of Medicine, University of Miami, FL; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine, Epidemiology, Health Services, Department of Biostatistics (E.W.), and Division of Medical Genetics (E.W.), Department of Medicine, University of Washington, Seattle; Department of Biostatistics (S.-H.C., A.D., L.A.F.), Boston University School of Public Health, MA; The Framingham Heart Study (A.D., S.S.), MA; Department of Neurology (A.D., L.A.F., S.S.), Boston University School of Medicine, MA; Department of Epidemiology (C.M.v.D), Erasmus MC, Rotterdam, Netherlands; Brown Foundation Institute of Molecular Medicine (M.F.) and Human Genetics Center (M.F.), University of Texas Health Science Center, Houston; The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology (S.B.G.), Cambridge; Harvard University (S.B.G.), Cambridge, MA; The McDonnell Genome Institute (D.C.K., D.E.L.) and Department of Genetics (D.E.L.), Washington University, St. Louis, MO; Department of Biostatistics and Epidemiology (A.C.N.) and Perelman School of Medicine (G.S.), University of Pennsylvania, Philadelphia; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Human Genome Sequencing Center (W.S., E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology and Biostatistics (W.S.B., J.L.H.), Case Western Reserve University, Cleveland, OH; Department of Medical and Molecular Genetics (T.M.F.), Indiana University School of Medicine, Indianapolis; Department of Medicine (Biomedical Genetics) (L.A.F.), Department of Ophthalmology (L.A.F.), and Department of Epidemiology (L.A.F.), Boston University School of Medicine and Public Health, MA; Department of Neuroscience (A.G.), Icahn School of Medicine at Mount Sinai, New York, NY; Human Genetics Center (E.B.), UT Health School of Public Health, Houston, TX; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (R.M.) and Gertrude H. Sergievsky Center (R.M.), Columbia University Medical Center, New York, NY; Department of Neurology (R.M.), Columbia University Medical Center and New York Presbyterian Hospital, NY; and Department of Epidemiology (R.M.), Mailman School of Public Health, Columbia University, New York, NY
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Pant A, Pasupureddy R, Pande V, Seshadri S, Dixit R, Pandey KC. Proteases in Mosquito Borne Diseases: New Avenues in Drug Development. Curr Top Med Chem 2017; 17:2221-2232. [PMID: 28137230 DOI: 10.2174/1568026617666170130122231] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2016] [Revised: 09/12/2016] [Accepted: 10/27/2016] [Indexed: 02/08/2023]
Abstract
INTRODUCTION Mosquito borne diseases continue to propagate and cause millions of deaths annually. They are caused either by protozoan parasites such as Plasmodium, Toxoplasma or by flaviviruses including Dengue and Zika. Among the proteome of such parasitic organisms, proteases play essential roles in events such as host invasion, hemoglobin hydrolysis, replication and immune evasion. Plasmepsin V (PMV), an endoplasmic reticulum resident aspartic protease of Plasmodium spp., is involved in the export of ~400 proteins containing the conserved Plasmodium Export Element motif (PEXEL). Interactions and cleavage of PEXEL proteins by PM V is necessary for export to and across the parasitophorous vacuole membrane. Protease System: Similarly in flaviviruses, a two-component protease system consisting of nonstructural proteins, NS2B and NS3, interacts with other non-structural proteins and plays a major role in viral replication, polyprotein cleavage and virion particle assembly. Thus, proteases involved in indispensable roles in pathogen machinery can be considered as attractive drug targets. Inhibitors against proteases are being used in clinical trials for other communicable and non-communicable diseases. Currently, hydroxyethylamine based inhibitors targeting the catalytic site of PM V with picomolar inhibitory concentrations have been tested in vitro. CONCLUSION For recently characterized disease such as Zika, no known treatments exist while compound such as Policresulen has high affinity for Dengue NS2B/NS3 complex. Understanding proteases structure-function relationship and protease-inhibitor interactions can provide new insights for novel chemotherapeutic strategies.
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Affiliation(s)
- A Pant
- National Institute of Malaria Research, Dwarka Sector - 8, New Delhi - 110077, India,Department of Biotechnology, Kumaun University, Nainital, Uttarakhand – 263001, India
| | - R Pasupureddy
- National Institute of Malaria Research, Dwarka Sector - 8, New Delhi - 110077, India,Institute of Science, Nirma University, SG Highway, Ahmedabad, Gujarat - 382481, India
| | - V Pande
- Department of Biotechnology, Kumaun University, Nainital, Uttarakhand – 263001, India
| | - S Seshadri
- Institute of Science, Nirma University, SG Highway, Ahmedabad, Gujarat - 382481, India
| | - R Dixit
- National Institute of Malaria Research, Dwarka Sector - 8, New Delhi - 110077, India
| | - K C Pandey
- Department of Biochemistry, National Institute for Research in Environmental Health, Bhopal, MP - 462001, India
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Ramakrishnan D, Chidambarathanu S, Murli L, Micheal J, Jagadeesh S, Suresh I, Seshadri S. Persistent Left Superior Vena Cava in Fetuses: An Autopsy Series. Fetal Pediatr Pathol 2017; 36:304-310. [PMID: 28569558 DOI: 10.1080/15513815.2017.1324546] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
OBJECTIVE To review fetal autopsy reports with persistent left superior vena cava (PLSVC) and identify its associations. MATERIALS AND METHODS Autopsy reports of all fetuses diagnosed with PLSVC in our center from January 2011 to December 2015 were reviewed. Fetuses less than 15 weeks gestational age along with autolyzed and damaged hearts were excluded from the study. The study group was compared with controls during this period. RESULTS Prenatal ultrasound detection rate of PLSVC was 13.06%. All the cases had associated anomalies of which 96% had extra cardiac anomalies and 67% had intrinsic cardiac defects among which septal defects were most common (39.6%). Anomalies of cardiovascular, respiratory, genitourinary and musculoskeletal, hypoplastic thymus and single umbilical artery were significantly higher in the study group. CONCLUSION This study emphasizes on the importance of improving the technical skill for imaging the three-vessel view as PLSVC seems to have significant associations.
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Affiliation(s)
- Uma Ram
- Seethapathy Hospital, Chennai, India
| | - Suresh Seshadri
- Mediscan Systems and Fetal Care Research Foundation, Chennai, India
| | - Ponnusamy Saravanan
- Populations, Evidence and Technologies, Warwick Medical School, University of Warwick, Coventry CV4 7AL, UK.
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Venkataraman H, Ram U, Craik S, Arungunasekaran A, Seshadri S, Saravanan P. Increased fetal adiposity prior to diagnosis of gestational diabetes in South Asians: more evidence for the 'thin-fat' baby. Diabetologia 2017; 60:399-405. [PMID: 27913848 PMCID: PMC6518087 DOI: 10.1007/s00125-016-4166-2] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2016] [Accepted: 11/07/2016] [Indexed: 12/17/2022]
Abstract
AIMS/HYPOTHESIS Gestational diabetes mellitus (GDM) is associated with an increased future risk of obesity in the offspring. Increased adiposity has been observed in the newborns of women with GDM. Our aim was to examine early fetal adiposity in women with GDM. METHODS Obstetric and sonographic data was collated for 153 women with GDM and 178 controls from a single centre in Chennai, India. Fetal head circumference (HC), abdominal circumference (AC), femur length (FL) and biparietal diameter (BPD) were recorded at 11, 20 and 32 weeks. Anterior abdominal wall thickness (AAWT) as a marker of abdominal adiposity at 20 and 32 weeks was compared between groups. Adjustments were made for maternal age, BMI, parity, gestational weight gain, fetal sex and gestational age. RESULTS Fetuses of women with GDM had significantly higher AAWT at 20 weeks (β 0.26 [95% CI 0.15, 0.37] mm, p < 0.0001) despite lower measures of HC, FL, BPD and AC. AAWT remained higher in the fetuses of women with GDM at 32 weeks (β 0.48 [0.30, 0.65] mm, p < 0.0001) despite similar measures for HC, FL, BPD and AC between groups. Both groups had similar birthweights at term. There was an independent relationship between fasting plasma glucose levels and AAWT after adjustment as described above. CONCLUSIONS/INTERPRETATION A 'thin but fat' phenotype signifying a disproportionate increase in adiposity despite smaller or similar lean body mass was observed in the fetuses of mothers with GDM, even at 20 weeks, thus pre-dating the biochemical diagnosis of GDM. Increased AAWT may serve as an early marker of GDM.
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Affiliation(s)
- Hema Venkataraman
- Populations, Evidence and Technologies, Division of Health Sciences, Warwick Medical School, University of Warwick, Gibbet Hill, Coventry, CV4 7AL, UK
| | - Uma Ram
- Seethapathy Clinic and Hospital, Chennai, India
| | - Sam Craik
- Populations, Evidence and Technologies, Division of Health Sciences, Warwick Medical School, University of Warwick, Gibbet Hill, Coventry, CV4 7AL, UK
| | | | | | - Ponnusamy Saravanan
- Populations, Evidence and Technologies, Division of Health Sciences, Warwick Medical School, University of Warwick, Gibbet Hill, Coventry, CV4 7AL, UK.
- Department of Diabetes, Endocrinology & Metabolism, George Eliot Hospital, Nuneaton, UK.
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Wataganara T, Seshadri S, Leung TY, Matter C, Ngerncham M, Triyasunant N, Mali PV, Biswas A, Nawapun K, Phithakwatchara N, Flake AW, Johnson MP, Biswas A, Choolani M. Establishing Prenatal Surgery for Myelomeningocele in Asia: The Singapore Consensus. Fetal Diagn Ther 2017; 41:161-178. [DOI: 10.1159/000452218] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2016] [Accepted: 10/04/2016] [Indexed: 11/19/2022]
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Jacob P, Srinath S, Girimaji S, Seshadri S, Sagar JV. Co-morbidity in Attention-Deficit Hyperactivity Disorder: A Clinical Study from India. East Asian Arch Psychiatry 2016; 26:148-153. [PMID: 28053283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
OBJECTIVE To assess the prevalence of neurodevelopmental and psychiatric co-morbidities in children and adolescents diagnosed with attention-deficit hyperactivity disorder at a tertiary care child and adolescent psychiatry centre. METHODS A total of 63 children and adolescents who were diagnosed with attention-deficit hyperactivity disorder and fulfilled the inclusion criteria were comprehensively assessed for neurodevelopmental and psychiatric co-morbidities. The tools used included the Mini-International Neuropsychiatric Interview for Children and Adolescents, Attention Deficit Hyperactivity Disorder Rating Scale IV (ADHD-RS), Children's Global Assessment Scale, Clinical Global Impression Scale, Vineland Social Maturity Scale, and Childhood Autism Rating Scale. RESULTS All except 1 subject had neurodevelopmental and / or psychiatric disorder co-morbid with attention-deficit hyperactivity disorder; 66.7% had both neurodevelopmental and psychiatric disorders. Specific learning disability was the most common co-existing neurodevelopmental disorder and oppositional defiant disorder was the most common psychiatric co-morbidity. The mean baseline ADHD-RS scores were significantly higher in the group with psychiatric co-morbidities, especially in the group with oppositional defiant disorder. CONCLUSION Co-morbidity is present at a very high frequency in clinic-referred children diagnosed with attention-deficit hyperactivity disorder. Psychiatric co-morbidity, specifically oppositional defiant disorder, has an impact on the severity of attention-deficit hyperactivity disorder. Co-morbidity needs to be explicitly looked for during evaluation and managed appropriately.
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Affiliation(s)
- P Jacob
- Department of Child and Adolescent Psychiatry, National Institute of Mental Health And Neuro Sciences, Bangalore, India
| | - S Srinath
- Department of Child and Adolescent Psychiatry, National Institute of Mental Health And Neuro Sciences, Bangalore, India
| | - S Girimaji
- Department of Child and Adolescent Psychiatry, National Institute of Mental Health And Neuro Sciences, Bangalore, India
| | - S Seshadri
- Department of Child and Adolescent Psychiatry, National Institute of Mental Health And Neuro Sciences, Bangalore, India
| | - J V Sagar
- Department of Child and Adolescent Psychiatry, National Institute of Mental Health And Neuro Sciences, Bangalore, India
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Beena S, Murlidhar L, Seshadri S, Jagadeesh S, Suresh I. Usefulness of fetal autopsy in the diagnosis of blomstrand chondrodysplasia: a report of three cases. J Matern Fetal Neonatal Med 2016; 30:1041-1044. [PMID: 27353973 DOI: 10.1080/14767058.2016.1199675] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Blomstrand osteochondrodysplasia (BOCD) is a rare autosomal recessive sclerosing skeletal dysplasia characterized by accelerated chondrocyte differentiation. In this article, we discuss three cases where lethal skeletal dysplasia was suspected and Blomstrand dysplasia was diagnosed by autopsy. Antenatal ultrasound findings include increased nuchal translucency, tetramicromelia and polyhydramnios. Radiological hallmark is advanced skeletal maturation and bone sclerosis. Histology of long bones revealed narrow cartilagenous cap and changes in the physeal growth zone which showed severe hypoplasia and disorganization of proliferative phase and hypertrophic phase. Homozygous and compound heterozygous mutations in PTHR1 gene have been implicated in the pathogenesis of this chondrodysplasia.
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Affiliation(s)
- Suresh Beena
- a Department of Clinical Genetics and Genetic Counseling
| | | | | | | | - Indrani Suresh
- e Department of Fetal Medicine , Mediscan Systems , Chennai , India
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41
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Ibrahim-Verbaas CA, Bressler J, Debette S, Schuur M, Smith AV, Bis JC, Davies G, Trompet S, Smith JA, Wolf C, Chibnik LB, Liu Y, Vitart V, Kirin M, Petrovic K, Polasek O, Zgaga L, Fawns-Ritchie C, Hoffmann P, Karjalainen J, Lahti J, Llewellyn DJ, Schmidt CO, Mather KA, Chouraki V, Sun Q, Resnick SM, Rose LM, Oldmeadow C, Stewart M, Smith BH, Gudnason V, Yang Q, Mirza SS, Jukema JW, deJager PL, Harris TB, Liewald DC, Amin N, Coker LH, Stegle O, Lopez OL, Schmidt R, Teumer A, Ford I, Karbalai N, Becker JT, Jonsdottir MK, Au R, Fehrmann RSN, Herms S, Nalls M, Zhao W, Turner ST, Yaffe K, Lohman K, van Swieten JC, Kardia SLR, Knopman DS, Meeks WM, Heiss G, Holliday EG, Schofield PW, Tanaka T, Stott DJ, Wang J, Ridker P, Gow AJ, Pattie A, Starr JM, Hocking LJ, Armstrong NJ, McLachlan S, Shulman JM, Pilling LC, Eiriksdottir G, Scott RJ, Kochan NA, Palotie A, Hsieh YC, Eriksson JG, Penman A, Gottesman RF, Oostra BA, Yu L, DeStefano AL, Beiser A, Garcia M, Rotter JI, Nöthen MM, Hofman A, Slagboom PE, Westendorp RGJ, Buckley BM, Wolf PA, Uitterlinden AG, Psaty BM, Grabe HJ, Bandinelli S, Chasman DI, Grodstein F, Räikkönen K, Lambert JC, Porteous DJ, Price JF, Sachdev PS, Ferrucci L, Attia JR, Rudan I, Hayward C, Wright AF, Wilson JF, Cichon S, Franke L, Schmidt H, Ding J, de Craen AJM, Fornage M, Bennett DA, Deary IJ, Ikram MA, Launer LJ, Fitzpatrick AL, Seshadri S, van Duijn CM, Mosley TH. GWAS for executive function and processing speed suggests involvement of the CADM2 gene. Mol Psychiatry 2016; 21:189-197. [PMID: 25869804 PMCID: PMC4722802 DOI: 10.1038/mp.2015.37] [Citation(s) in RCA: 103] [Impact Index Per Article: 12.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2013] [Revised: 01/21/2015] [Accepted: 02/11/2015] [Indexed: 01/20/2023]
Abstract
To identify common variants contributing to normal variation in two specific domains of cognitive functioning, we conducted a genome-wide association study (GWAS) of executive functioning and information processing speed in non-demented older adults from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) consortium. Neuropsychological testing was available for 5429-32,070 subjects of European ancestry aged 45 years or older, free of dementia and clinical stroke at the time of cognitive testing from 20 cohorts in the discovery phase. We analyzed performance on the Trail Making Test parts A and B, the Letter Digit Substitution Test (LDST), the Digit Symbol Substitution Task (DSST), semantic and phonemic fluency tests, and the Stroop Color and Word Test. Replication was sought in 1311-21860 subjects from 20 independent cohorts. A significant association was observed in the discovery cohorts for the single-nucleotide polymorphism (SNP) rs17518584 (discovery P-value=3.12 × 10(-8)) and in the joint discovery and replication meta-analysis (P-value=3.28 × 10(-9) after adjustment for age, gender and education) in an intron of the gene cell adhesion molecule 2 (CADM2) for performance on the LDST/DSST. Rs17518584 is located about 170 kb upstream of the transcription start site of the major transcript for the CADM2 gene, but is within an intron of a variant transcript that includes an alternative first exon. The variant is associated with expression of CADM2 in the cingulate cortex (P-value=4 × 10(-4)). The protein encoded by CADM2 is involved in glutamate signaling (P-value=7.22 × 10(-15)), gamma-aminobutyric acid (GABA) transport (P-value=1.36 × 10(-11)) and neuron cell-cell adhesion (P-value=1.48 × 10(-13)). Our findings suggest that genetic variation in the CADM2 gene is associated with individual differences in information processing speed.
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Affiliation(s)
- CA Ibrahim-Verbaas
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus
University Medical Center, Rotterdam, The Netherlands,Department of Neurology, Erasmus University Medical Center,
Rotterdam, The Netherlands,Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - J Bressler
- Human Genetics Center, School of Public Health, University of
Texas Health Science Center at Houston, Houston, TX, USA,Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - S Debette
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA,Institut National de la Santé et de la Recherche
Médicale (INSERM), U897, Epidemiology and Biostatistics, University of Bordeaux,
Bordeaux, France,Department of Neurology, Bordeaux University Hospital, Bordeaux,
France,Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - M Schuur
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus
University Medical Center, Rotterdam, The Netherlands,Department of Neurology, Erasmus University Medical Center,
Rotterdam, The Netherlands,Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - AV Smith
- Icelandic Heart Association, Kopavogur, Iceland,Faculty of Medicine, University of Iceland, Reykjavik,
Iceland,Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - JC Bis
- Cardiovascular Health Research Unit, Department of Medicine,
University of Washington, Seattle, WA, USA,Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - G Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK,Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - S Trompet
- Department of Cardiology, Leiden University Medical Center,
Leiden, The Netherlands,Department of Gerontology and Geriatrics, Leiden University
Medical Center, Leiden, The Netherlands
| | - JA Smith
- Department of Epidemiology, University of Michigan, Ann Arbor,
MI, USA
| | - C Wolf
- RG Statistical Genetics, Max Planck Institute of Psychiatry,
Munich, Germany
| | - LB Chibnik
- Program in Translational Neuropsychiatric Genomics, Department
of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - Y Liu
- Department of Epidemiology, Wake Forest School of Medicine,
Winston-Salem, NC, USA
| | - V Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular
Medicine, University of Edinburgh, Edinburgh, UK
| | - M Kirin
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - K Petrovic
- Department of Neurology, Medical University and General
Hospital of Graz, Graz, Austria
| | - O Polasek
- Department of Public Health, University of Split, Split,
Croatia
| | - L Zgaga
- Department of Public Health and Primary Care, Trinity College
Dublin, Dublin, Ireland
| | - C Fawns-Ritchie
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK
| | - P Hoffmann
- Institute of Neuroscience and Medicine (INM -1), Research
Center Juelich, Juelich, Germany,Division of Medical Genetics, Department of Biomedicine,
University of Basel, Basel, Switzerland,Department of Genomics, Life and Brain Research Center,
Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - J Karjalainen
- Department of Genetics, University Medical Centre Groningen,
University of Groningen, Groningen, The Netherlands
| | - J Lahti
- Institute of Behavioural Sciences, University of Helsinki,
Helsinki, Finland,Folkhälsan Research Centre, Helsinki, Finland
| | - DJ Llewellyn
- Institute of Biomedical and Clinical Sciences, University of
Exeter Medical School, Exeter, UK
| | - CO Schmidt
- Institute for Community Medicine, University Medicine
Greifswald, Greifswald, Germany
| | - KA Mather
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW
Medicine, University of New South Wales, Sydney, Australia
| | - V Chouraki
- Inserm, U1167, Institut Pasteur de Lille, Université
Lille-Nord de France, Lille, France
| | - Q Sun
- Channing Division of Network Medicine, Department of Medicine,
Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - SM Resnick
- Laboratory of Behavioral Neuroscience, National Institute on
Aging, NIH, Baltimore, MD, USA
| | - LM Rose
- Division of Preventive Medicine, Brigham and Women's Hospital,
Boston, MA, USA
| | - C Oldmeadow
- Hunter Medical Research Institute and Faculty of Health,
University of Newcastle, Newcastle, NSW, Australia
| | - M Stewart
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - BH Smith
- Medical Research Institute, University of Dundee, Dundee,
UK
| | - V Gudnason
- Icelandic Heart Association, Kopavogur, Iceland,Faculty of Medicine, University of Iceland, Reykjavik,
Iceland
| | - Q Yang
- The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA,Department of Biostatistics, Boston University School of Public
Health, Boston, MA, USA
| | - SS Mirza
- Department of Epidemiology, Erasmus University Medical Center,
Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The
Netherlands
| | - JW Jukema
- Department of Cardiology, Leiden University Medical Center,
Leiden, The Netherlands
| | - PL deJager
- Program in Translational Neuropsychiatric Genomics, Department
of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - TB Harris
- Laboratory of Epidemiology and Population Sciences, National
Institute on Aging, Bethesda, MD, USA
| | - DC Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh,
UK
| | - N Amin
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus
University Medical Center, Rotterdam, The Netherlands
| | - LH Coker
- Division of Public Health Sciences and Neurology, Wake Forest
School of Medicine, Winston-Salem, NC, USA
| | - O Stegle
- Max Planck Institute for Developmental Biology, Max Planck
Institute for Intelligent Systems, Tübingen, Germany
| | - OL Lopez
- Department of Neurology, University of Pittsburgh, Pittsburgh,
PA, USA
| | - R Schmidt
- Department of Neurology, Medical University and General
Hospital of Graz, Graz, Austria
| | - A Teumer
- Interfaculty Institute for Genetics and Functional Genomics,
University Medicine Greifswald, Greifswald, Germany
| | - I Ford
- Robertson Center for biostatistics, University of Glasgow,
Glasgow, UK
| | - N Karbalai
- RG Statistical Genetics, Max Planck Institute of Psychiatry,
Munich, Germany
| | - JT Becker
- Department of Neurology, University of Pittsburgh, Pittsburgh,
PA, USA,Department of Psychiatry, University of Pittsburgh, Pittsburgh,
PA, USA,Department of Psychology, University of Pittsburgh, Pittsburgh,
PA, USA
| | | | - R Au
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA,The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA
| | - RSN Fehrmann
- Department of Genetics, University Medical Centre Groningen,
University of Groningen, Groningen, The Netherlands
| | - S Herms
- Division of Medical Genetics, Department of Biomedicine,
University of Basel, Basel, Switzerland,Department of Genomics, Life and Brain Research Center,
Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - M Nalls
- Laboratory of Neurogenetics, National Institute on Aging,
Bethesda, MD, USA
| | - W Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor,
MI, USA
| | - ST Turner
- Division of Nephrology and Hypertension, Department of Internal
Medicine, Mayo Clinic, Rochester, MN, USA
| | - K Yaffe
- Departments of Psychiatry, Neurology and Epidemiology,
University of California, San Francisco and San Francisco VA Medical Center, San Francisco,
CA, USA
| | - K Lohman
- Department of Epidemiology, Wake Forest School of Medicine,
Winston-Salem, NC, USA
| | - JC van Swieten
- Department of Neurology, Erasmus University Medical Center,
Rotterdam, The Netherlands
| | - SLR Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor,
MI, USA
| | - DS Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - WM Meeks
- Department of Medicine, Division of Geriatrics, University of
Mississippi Medical Center, Jackson, MS, USA
| | - G Heiss
- Department of Epidemiology, Gillings School of Global Public
Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - EG Holliday
- Hunter Medical Research Institute and Faculty of Health,
University of Newcastle, Newcastle, NSW, Australia
| | - PW Schofield
- School of Medicine and Public Health, Faculty of Health,
University of Newcastle, Newcastle, SW, Australia
| | - T Tanaka
- Translational Gerontology Branch, National Institute on Aging,
Baltimore, MD, USA
| | - DJ Stott
- Department of Cardiovascular and Medical Sciences, University
of Glasgow, Glasgow, UK
| | - J Wang
- Department of Biostatistics, Boston University School of Public
Health, Boston, MA, USA
| | - P Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital,
Boston, MA, USA
| | - AJ Gow
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh,
UK
| | - A Pattie
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK
| | - JM Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK,Alzheimer Scotland Research Centre, Edinburgh, UK
| | - LJ Hocking
- Division of Applied Medicine, University of Aberdeen, Aberdeen,
UK
| | - NJ Armstrong
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW
Medicine, University of New South Wales, Sydney, Australia,Cancer Research Program, Garvan Institute of Medical Research,
Sydney, NSW, Australia,School of Mathematics & Statistics and Prince of Wales
Clinical School, University of New South Wales, Sydney, NSW, Australia
| | - S McLachlan
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - JM Shulman
- Department of Neurology, Baylor College of Medicine, Houston,
TX, USA,Department of Molecular and Human Genetics, The Jan and Dan
Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA
| | - LC Pilling
- Epidemiology and Public Health Group, University of Exeter
Medical School, Exeter, UK
| | | | - RJ Scott
- Hunter Medical Research Institute and Faculty of Health,
University of Newcastle, Newcastle, NSW, Australia
| | - NA Kochan
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW
Medicine, University of New South Wales, Sydney, Australia,Neuropsychiatric Institute, The Prince of Wales Hospital,
Sydney, NSW, Australia
| | - A Palotie
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus,
Cambridge, UK,Institute for Molecular Medicine Finland (FIMM), University of
Helsinki, Helsinki, Finland,Department of Medical Genetics, University of Helsinki and
University Central Hospital, Helsinki, Finland
| | - Y-C Hsieh
- School of Public Health, Taipei Medical University, Taipei,
Taiwan
| | - JG Eriksson
- Folkhälsan Research Centre, Helsinki, Finland,Department of General Practice and Primary Health Care,
University of Helsinki, Helsinki, Finland,National Institute for Health and Welfare, Helsinki,
Finland,Helsinki University Central Hospital, Unit of General Practice,
Helsinki, Finland,Vasa Central Hospital, Vasa, Finland
| | - A Penman
- Center of Biostatistics and Bioinformatics, University of
Mississippi Medical Center, Jackson, MS, USA
| | - RF Gottesman
- Department of Neurology, Johns Hopkins University School of
Medicine, Baltimore, MD, USA
| | - BA Oostra
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus
University Medical Center, Rotterdam, The Netherlands
| | - L Yu
- Rush Alzheimer's Disease Center, Rush University Medical
Center, Chicago, IL, USA
| | - AL DeStefano
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA,The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA,Department of Biostatistics, Boston University School of Public
Health, Boston, MA, USA
| | - A Beiser
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA,The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA,Department of Biostatistics, Boston University School of Public
Health, Boston, MA, USA
| | - M Garcia
- Laboratory of Epidemiology and Population Sciences, National
Institute on Aging, Bethesda, MD, USA
| | - JI Rotter
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los
Angeles, CA, USA,Institute for Translational Genomics and Population Sciences,
Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA,
USA,Division of Genetic Outcomes, Department of Pediatrics,
Harbor-UCLA Medical Center, Torrance, CA, USA
| | - MM Nöthen
- Department of Genomics, Life and Brain Research Center,
Institute of Human Genetics, University of Bonn, Bonn, Germany,German Center for Neurodegenerative Diseases (DZNE), Bonn,
Germany
| | - A Hofman
- Department of Epidemiology, Erasmus University Medical Center,
Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The
Netherlands
| | - PE Slagboom
- Department of Molecular Epidemiology, Leiden University Medical
Center, Leiden, The Netherlands
| | - RGJ Westendorp
- Leiden Academy of Vitality and Ageing, Leiden, The
Netherlands
| | - BM Buckley
- Department of Pharmacology and Therapeutics, University College
Cork, Cork, Ireland
| | - PA Wolf
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA,The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA
| | - AG Uitterlinden
- Department of Epidemiology, Erasmus University Medical Center,
Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The
Netherlands,Department of Internal Medicine, Erasmus University Medical
Center, Rotterdam, The Netherlands
| | - BM Psaty
- Cardiovascular Health Research Unit, Department of Medicine,
University of Washington, Seattle, WA, USA,Department of Epidemiology, University of Washington, Seattle,
WA, USA,Department of Health Services, University of Washington,
Seattle, WA, USA,Group Health Research Institute, Group Health, Seattle, WA,
USA
| | - HJ Grabe
- Department of Psychiatry and Psychotherapy, University Medicine
Greifswald, HELIOS-Hospital Stralsund, Stralsund, Germany
| | - S Bandinelli
- Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - DI Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital,
Boston, MA, USA
| | - F Grodstein
- Channing Division of Network Medicine, Department of Medicine,
Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - K Räikkönen
- Institute of Behavioural Sciences, University of Helsinki,
Helsinki, Finland
| | - J-C Lambert
- Inserm, U1167, Institut Pasteur de Lille, Université
Lille-Nord de France, Lille, France
| | - DJ Porteous
- Centre for Genomic and Experimental Medicine, Institute of
Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | | | - JF Price
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - PS Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW
Medicine, University of New South Wales, Sydney, Australia,Neuropsychiatric Institute, The Prince of Wales Hospital,
Sydney, NSW, Australia
| | - L Ferrucci
- Translational Gerontology Branch, National Institute on Aging,
Baltimore, MD, USA
| | - JR Attia
- Hunter Medical Research Institute and Faculty of Health,
University of Newcastle, Newcastle, NSW, Australia
| | - I Rudan
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - C Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular
Medicine, University of Edinburgh, Edinburgh, UK
| | - AF Wright
- MRC Human Genetics Unit, Institute of Genetics and Molecular
Medicine, University of Edinburgh, Edinburgh, UK
| | - JF Wilson
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - S Cichon
- Division of Medical Genetics, Department of Biomedicine,
University of Basel, Basel, Switzerland,Department of Genomics, Life and Brain Research Center,
Institute of Human Genetics, University of Bonn, Bonn, Germany,Institute of Neuroscience and Medicine (INM-1), Research Center
Juelich, Juelich, Germany
| | - L Franke
- Department of Genetics, University Medical Centre Groningen,
University of Groningen, Groningen, The Netherlands
| | - H Schmidt
- Department of Neurology, Medical University and General
Hospital of Graz, Graz, Austria
| | - J Ding
- Department of Internal Medicine, Wake Forest University School
of Medicine, Winston-Salem, NC, USA
| | - AJM de Craen
- Department of Gerontology and Geriatrics, Leiden University
Medical Center, Leiden, The Netherlands
| | - M Fornage
- Institute for Molecular Medicine and Human Genetics Center,
University of Texas Health Science Center at Houston, Houston, TX, USA
| | - DA Bennett
- Rush Alzheimer's Disease Center, Rush University Medical
Center, Chicago, IL, USA
| | - IJ Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh,
UK
| | - MA Ikram
- Department of Neurology, Erasmus University Medical Center,
Rotterdam, The Netherlands,Department of Epidemiology, Erasmus University Medical Center,
Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The
Netherlands,Department of Radiology, Erasmus University Medical Center,
Rotterdam, The Netherlands
| | - LJ Launer
- Laboratory of Epidemiology and Population Sciences, National
Institute on Aging, Bethesda, MD, USA
| | - AL Fitzpatrick
- Department of Epidemiology, University of Washington, Seattle,
WA, USA
| | - S Seshadri
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA,The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA
| | - CM van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus
University Medical Center, Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The
Netherlands
| | - TH Mosley
- Department of Medicine and Neurology, University of Mississippi
Medical Center, Jackson, MS, USA
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Sahani AK, Joseph J, Radhakrishnan R, Sivaprakasam M, Seshadri S. Comparison of measurement of the augmentation index from ARTSENS and eTRACKING. Biomed Phys Eng Express 2016. [DOI: 10.1088/2057-1976/2/1/015007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Rajesh P, Gunasekaran S, Gnanasambandan T, Seshadri S. Experimental and theoretical study of ornidazole. Spectrochim Acta A Mol Biomol Spectrosc 2016; 153:496-504. [PMID: 26408856 DOI: 10.1016/j.saa.2015.08.032] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2014] [Revised: 08/08/2015] [Accepted: 08/14/2015] [Indexed: 06/05/2023]
Abstract
The Fourier transform infrared (FT-IR) and the Fourier transform Raman (FT-Raman) spectra of the title molecule in solid phase were recorded in the region 4000-400 cm(-1) and 4000-100 cm(-1) respectively. The geometrical parameters and energies were investigated with the help of Density Functional Theory (DFT) employing B3LYP method and 6-31G (d, p) basis set. The analysis was supported by electrostatic potential maps and calculation of HOMO-LUMO. UV, FT-IR and FT-Raman spectra of ornidazole were calculated and compared with experimental results. Thermodynamic properties like entropy, heat capacity, have been calculated for the molecule. The predicted first hyperpolarizability also shows that the molecule might have a reasonably good non-linear optical (NLO) behavior. The intramolecular contacts have been interpreted using natural bond orbital (NBO) and natural localized molecular orbital (NLMO) analysis.
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Affiliation(s)
- P Rajesh
- Department of Physics, Pachaiyappa's College, Chennai 600030, India; Department of Physics, Meenakshi Academy of Higher Education & Research, Faculty of Humanities and Science, Meenakshi University, Chennai-600078, India.
| | - S Gunasekaran
- Research & Development, St. Peter's University, Avadi, Chennai 600 054, India
| | - T Gnanasambandan
- Department of Physics, Pallavan College of Engineering, Kanchipuram 63150, India
| | - S Seshadri
- Department of Physics, L.N. Govt. Arts College, Ponneri 601204, India
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44
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Kano S, Yuan M, Cardarelli RA, Maegawa G, Higurashi N, Gaval-Cruz M, Wilson AM, Tristan C, Kondo MA, Chen Y, Koga M, Obie C, Ishizuka K, Seshadri S, Srivastava R, Kato TA, Horiuchi Y, Sedlak TW, Lee Y, Rapoport JL, Hirose S, Okano H, Valle D, O'Donnell P, Sawa A, Kai M. Clinical utility of neuronal cells directly converted from fibroblasts of patients for neuropsychiatric disorders: studies of lysosomal storage diseases and channelopathy. Curr Mol Med 2015; 15:138-45. [PMID: 25732146 DOI: 10.2174/1566524015666150303110300] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2014] [Revised: 12/20/2014] [Accepted: 01/18/2015] [Indexed: 11/22/2022]
Abstract
Methodologies for generating functional neuronal cells directly from human fibroblasts [induced neuronal (iN) cells] have been recently developed, but the research so far has only focused on technical refinements or recapitulation of known pathological phenotypes. A critical question is whether this novel technology will contribute to elucidation of novel disease mechanisms or evaluation of therapeutic strategies. Here we have addressed this question by studying Tay-Sachs disease, a representative lysosomal storage disease, and Dravet syndrome, a form of severe myoclonic epilepsy in infancy, using human iN cells with feature of immature postmitotic glutamatergic neuronal cells. In Tay-Sachs disease, we have successfully characterized canonical neuronal pathology, massive accumulation of GM2 ganglioside, and demonstrated the suitability of this novel cell culture for future drug screening. In Dravet syndrome, we have identified a novel functional phenotype that was not suggested by studies of classical mouse models and human autopsied brains. Taken together, the present study demonstrates that human iN cells are useful for translational neuroscience research to explore novel disease mechanisms and evaluate therapeutic compounds. In the future, research using human iN cells with well-characterized genomic landscape can be integrated into multidisciplinary patient-oriented research on neuropsychiatric disorders to address novel disease mechanisms and evaluate therapeutic strategies.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - A Sawa
- Departments of Psychiatry and Behavioral Sciences and Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
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45
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Manickam K, Reddy MR, Seshadri S, Raghavan B. Development of a training phantom for compression breast elastography-comparison of various elastography systems and numerical simulations. J Med Imaging (Bellingham) 2015; 2:047002. [PMID: 26697511 DOI: 10.1117/1.jmi.2.4.047002] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2015] [Accepted: 11/16/2015] [Indexed: 12/21/2022] Open
Abstract
The elastic properties of tissue are related to tissue composition and pathological changes. It has been observed that many pathological processes increase the elastic modulus of soft tissue compared to normal. Ultrasound compression elastography is a method of characterization of elastic properties that has been the focus of many research efforts in the last two decades. In medical radiology, compression elastography is provided as an additional tool with ultrasound B-mode in the existing scanners, and the combined features of elastography and echography act as a promising diagnostic method in breast cancer detection. However, the full capability of the ultrasound elastography technique together with B-mode has not been utilized by novice radiologists due to the nonavailability of suitable, appropriately designed tissue-mimicking phantoms. Since different commercially available ultrasound elastographic scanners follow their own unique protocols, training novice radiologists is becoming cumbersome. The main focus of this work is to develop a tissue-like agar-based phantom, which mimics breast tissue with common abnormal lesions like fibroadenoma and invasive ductal carcinoma in a clinically perceived way and compares the sonographic and elastographic appearances using different commercially available systems. In addition, the developed phantoms are simulated using the finite-element method, and ideal strain images are generated. Strain images from experiment and simulation are compared based on image contrast parameters, namely contrast transfer efficiency (CTE) and observed strain, and they are in good agreement. The strain image contrast of malignant inclusions is significantly improved compared to benign inclusions, and the trend of CTE is similar for all elastographic scanners under investigation.
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Affiliation(s)
- Kavitha Manickam
- Biomedical Engineering Group , Department of Applied Mechanics, IIT Madras, Chennai 600 036, India
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46
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Olson NC, Butenas S, Lange LA, Lange EM, Cushman M, Jenny NS, Walston J, Souto JC, Soria JM, Chauhan G, Debette S, Longstreth WT, Seshadri S, Reiner AP, Tracy RP. Coagulation factor XII genetic variation, ex vivo thrombin generation, and stroke risk in the elderly: results from the Cardiovascular Health Study. J Thromb Haemost 2015; 13:1867-77. [PMID: 26286125 PMCID: PMC4946166 DOI: 10.1111/jth.13111] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2015] [Revised: 06/12/2015] [Accepted: 08/02/2015] [Indexed: 12/31/2022]
Abstract
BACKGROUND The relationships of thrombin generation (TG) with cardiovascular disease risk are underevaluated in population-based cohorts. OBJECTIVES To evaluate the relationships of TG influenced by the contact and tissue factor coagulation pathways ex vivo with common single-nucleotide polymorphisms (SNPs) and incident cardiovascular disease and stroke. PATIENTS/METHODS We measured peak TG (pTG) in baseline plasma samples of Cardiovascular Health Study participants (n = 5411), both with and without inhibitory anti-factor XIa antibody (pTG/FXIa(-) ). We evaluated their associations with ~ 50 000 SNPs by using the IBCv2 genotyping array, and with incident cardiovascular disease and stroke events over a median follow-up of 13.2 years. RESULTS The minor allele for an SNP in the FXII gene (F12), rs1801020, was associated with lower pTG in European-Americans (β = - 34.2 ± 3.5 nm; P = 3.3 × 10(-22) ; minor allele frequency [MAF] = 0.23) and African-Americans (β = - 31.1 ± 7.9 nm; P = 9.0 × 10(-5) ; MAF = 0.42). Lower FXIa-independent pTG (pTG/FXIa(-) ) was associated with the F12 rs1801020 minor allele, and higher pTG/FXIa(-) was associated with the ABO SNP rs657152 minor allele (β = 16.3 nm; P = 4.3 × 10(-9) ; MAF = 0.37). The risk factor-adjusted ischemic stroke hazard ratios were 1.09 (95% confidence interval CI 1.01-1.17; P = 0.03) for pTG, 1.06 (95% CI 0.98-1.15; P = 0.17) for pTG/FXIa(-) , and 1.11 (95% CI 1.02-1.21; P = 0.02) for FXIa-dependent pTG (pTG/FXIa(+) ), per one standard deviation increment (n = 834 ischemic strokes). In a multicohort candidate gene analysis, rs1801020 was not associated with incident ischemic stroke (β = - 0.02; standard error = 0.08; P = 0.81). CONCLUSIONS These results support the importance of contact activation pathway-dependent TG as a risk factor for ischemic stroke, and indicate the importance of F12 SNPs for TG ex vivo and in vivo.
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Affiliation(s)
- N C Olson
- Department of Pathology and Laboratory Medicine, University of Vermont College of Medicine, Burlington, VT, USA
| | - S Butenas
- Department of Biochemistry, University of Vermont College of Medicine, Burlington, VT, USA
| | - L A Lange
- Department of Genetics, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - E M Lange
- Department of Genetics, University of North Carolina School of Medicine, Chapel Hill, NC, USA
- Department of Biostatistics, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - M Cushman
- Department of Pathology and Laboratory Medicine, University of Vermont College of Medicine, Burlington, VT, USA
- Department of Medicine, University of Vermont College of Medicine, Burlington, VT, USA
| | - N S Jenny
- Department of Pathology and Laboratory Medicine, University of Vermont College of Medicine, Burlington, VT, USA
| | - J Walston
- Division of Geriatric Medicine and Gerontology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - J C Souto
- Department of Hematology, Institute of Biomedical Research (IIB-Sant Pau), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - J M Soria
- Unit of Genomics of Complex Diseases, Institute of Biomedical Research (IIB-Sant Pau), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - G Chauhan
- INSERM U897, University of Bordeaux, Bordeaux, France
- University of Bordeaux, Bordeaux, France
| | - S Debette
- INSERM U897, University of Bordeaux, Bordeaux, France
- University of Bordeaux, Bordeaux, France
- Bordeaux University Hospital, Bordeaux, France
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - W T Longstreth
- Department of Neurology, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - S Seshadri
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - A P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - R P Tracy
- Department of Pathology and Laboratory Medicine, University of Vermont College of Medicine, Burlington, VT, USA
- Department of Biochemistry, University of Vermont College of Medicine, Burlington, VT, USA
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47
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Ghaisas SD, Seshadri S, Suresh B. Outcome of Antenatally Diagnosed Cardiac Rhabdomyoma: Case Series from a Tertiary Fetal Medicine Center in India. J Fetal Med 2015. [DOI: 10.1007/s40556-015-0042-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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48
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Agbenyikey W, Karasek R, Cifuentes M, Wolf PA, Seshadri S, Taylor JA, Beiser AS, Au R. Job strain and cognitive decline: a prospective study of the framingham offspring cohort. Int J Occup Environ Med 2015; 6:79-94. [PMID: 25890602 PMCID: PMC5282587 DOI: 10.15171/ijoem.2015.534] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/23/2014] [Accepted: 02/02/2015] [Indexed: 11/09/2022]
Abstract
BACKGROUND Workplace stress is known to be related with many behavioral and disease outcomes. However, little is known about its prospective relationship with measures of cognitive decline. OBJECTIVE To investigate the association of job strain, psychological demands and job control on cognitive decline. METHODS Participants from Framingham Offspring cohort (n=1429), were assessed on job strain, and received neuropsychological assessment approximately 15 years and 21 years afterwards. RESULTS High job strain and low control were associated with decline in verbal learning and memory. Job strain was associated with decline in word recognition skills. Active job and passive job predicted decline in verbal learning and memory relative to low strain jobs in the younger subgroup. Active job and demands were positively associated with abstract reasoning skills. CONCLUSIONS Job strain and job control may influence decline in cognitive performance.
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Affiliation(s)
- W Agbenyikey
- Department of Environmental and Occupational Health, Drexel University, Philadelphia, PA, USA.
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Raj RK, Gunasekaran S, Gnanasambandan T, Seshadri S. Combined spectroscopic and DFT studies on 6-bromo-4-chloro-3-formyl coumarin. Spectrochim Acta A Mol Biomol Spectrosc 2015; 139:505-514. [PMID: 25576949 DOI: 10.1016/j.saa.2014.12.024] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2014] [Revised: 11/16/2014] [Accepted: 12/09/2014] [Indexed: 06/04/2023]
Abstract
The FTIR and FT-Raman spectra of 6-bromo-4-chloro-3-formyl coumarin (6B4C3FC) have been recorded in the region 4000-400 and 4000-100 cm(-1), respectively. The optimized geometry, frequency and intensity of the vibrational bands were obtained by the density functional theory (DFT) using 6-31G(d,p) basis set. The harmonic vibrational frequencies were scaled and compared with experimental values. The observed and the calculated frequencies were found to be in good agreement. The UV-Visible spectrum was also recorded and compared with the theoretical values. The calculated HOMO and LUMO energies show that charge transfer occurs within molecule. The first order hyperpolarizability (β0) of 6B4C3FC is 21 times greater than that of urea. Stability of the molecule arising from hyperconjugative interactions, charge delocalization have been analyzed using natural bond orbital (NBO) analysis. Information about the charge density distribution of the molecule and its chemical reactivity has been obtained by mapping molecular electrostatic potential surface. In addition, the non-linear optical properties were discussed from the dipole moment values and the excitation wavelength in the UV-Visible region.
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Affiliation(s)
- R K Raj
- Department of Physics, SCSVMV University, Enathur, Kanchipuram 631561, India; Department of Physics, Pachaiyappa's College for Men, Kanchipuram 631 503, India.
| | - S Gunasekaran
- Research & Development, St. Peter's University, Avadi, Chennai 600 054, India
| | - T Gnanasambandan
- Department of Physics, Pallavan College of Engineering, Kanchipuram 631 502, India
| | - S Seshadri
- Department of Physics, L.N. Govt. Arts College, Ponneri, India
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Saravanan RR, Seshadri S, Gunasekaran S, Mendoza-Meroño R, Garcia-Granda S. Conformational analysis, X-ray crystallographic, FT-IR, FT-Raman, DFT, MEP and molecular docking studies on 1-(1-(3-methoxyphenyl) ethylidene) thiosemicarbazide. Spectrochim Acta A Mol Biomol Spectrosc 2015; 139:321-328. [PMID: 25574651 DOI: 10.1016/j.saa.2014.12.026] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2014] [Revised: 11/22/2014] [Accepted: 12/10/2014] [Indexed: 06/04/2023]
Abstract
Conformational analysis, X-ray crystallographic, FT-IR, FT-Raman, DFT, MEP and molecular docking studies on 1-(1-(3-methoxyphenyl) ethylidene) thiosemicarbazide (MPET) are investigated. From conformational analysis the examination of the positions of a molecule taken and the energy changes is observed. The docking studies of the ligand MPET with target protein showed that this is a good molecule which docks well with target related to HMG-CoA. Hence MPET can be considered for developing into a potent anti-cholesterol drug. MEP assists in optimization of electrostatic interactions between the protein and the ligand. The MEP surface displays the molecular shape, size and electrostatic potential values. The optimized geometry of the compound was calculated from the DFT-B3LYP gradient calculations employing 6-31G (d, p) basis set and calculated vibrational frequencies are evaluated via comparison with experimental values.
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Affiliation(s)
- R R Saravanan
- Department of Physics, Misrimal Navajee Munoth Jain Engineering College, Thoraipakkam, Chennai 600 097, India.
| | - S Seshadri
- Department of Physics, L.N. Govt. Arts College, Ponneri, Thiruvallur 601 001, India
| | - S Gunasekaran
- Research & Development, St. Peter's University, Avadi, Chennai 600 054, India
| | - R Mendoza-Meroño
- Faculty of Chemistry, Department of Physical and Analytical Chemistry, University Oviedo, C/ Julian Claveria, 8, 33006 Oviedo, Asturias, Spain
| | - S Garcia-Granda
- Faculty of Chemistry, Department of Physical and Analytical Chemistry, University Oviedo, C/ Julian Claveria, 8, 33006 Oviedo, Asturias, Spain
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