Control of confounding of genetic associations in stratified populations

Global and Local Ancestry and its Importance: A Review

The fastest way to significantly change the composition of a population is through admixture, an evolutionary mechanism. In animal breeding history, genetic admixture has provided both short-term and long-term advantages by utilizing the phenomenon of complementarity and heterosis in several traits and genetic diversity, respectively. The traditional method of admixture analysis by pedigree records has now been replaced greatly by genome-wide marker data that enables more precise estimations. Among these markers, SNPs have been the popular choice since they are cost-effective, not so laborious, and automation of genotyping is easy. Certain markers can suggest the possibility of a population's origin from a sample of DNA where the source individual is unknown or unwilling to disclose their lineage, which are called Ancestry-Informative Markers (AIMs). Revealing admixture level at the locus-specific level is termed as local ancestry and can be exploited to identify signs of recent selective response and can account for genetic drift. Considering the importance of genetic admixture and local ancestry, in this mini-review, both concepts are illustrated, encompassing basics, their estimation/identification methods, tools/software used and their applications.

Genetic predictors for bacterial vaginosis in women living with and at risk for HIV infection

PROBLEM

Bacterial vaginosis (BV) disproportionally impacts Black and Hispanic women, placing them at risk for HIV, sexually transmitted infections and preterm birth. It is unknown whether there are differences by genetic ancestry in BV risk or whether polymorphisms associated with BV risk differ by ancestry.

METHODS

Women's Interagency HIV Study (WIHS) participants with longitudinal Nugent scores were dichotomized as having (n = 319, Nugent 7-10) or not having BV (n = 367, Nugent 0-3). Genetic ancestry was defined by clustering of principal components from ancestry informative markers and further stratified by BV status. 627 single nucleotide polymorphisms (SNPs) across 41 genes important in mucosal defense were identified in the WIHS GWAS. A logistic regression analysis was adjusted for nongenetic predictors of BV and self-reported race/ethnicity to assess associations between genetic ancestry and genotype.

RESULTS

Self-reported race and genetic ancestry were associated with BV risk after adjustment for behavioral factors. Polymorphisms in mucosal defense genes including syndecans, cytokines and toll-like receptors (TLRs) were associated with BV in all ancestral groups.

CONCLUSIONS

The common association of syndecan, cytokine and TLR genes and the importance of immune function and inflammatory pathways in BV, suggests these should be targeted for further research on BV pathogenesis and therapeutics.

EGR3 Polymorphism Is a Potential Susceptibility Factor of Schizophrenia Risk in a Chinese Population

Objective: The purpose of this study was to evaluate the association between the single nucleotide polymorphisms (SNPs) (EGR3 rs1996147; EGR4 rs3813226, rs6747506; ERBB3 rs2292238; and ERBB4 rs707284, rs7560730) and the risk of schizophrenia (SZ) in a Chinese population. Materials and Methods: We conducted a case-control study, including 248 patients with SZ and 236 healthy controls matched for age and sex. The Mass-array platform was used to detect all the genotypes of the SNPs. Results: The results revealed that the EGR3 rs1996147 AA genotype was associated with borderline decreased SZ risk (AA vs. GG: adjusted OR = 0.43, 95% CI: 0.18-1.02, p = 0.06). However, no significant correlation was found between the other SNPs and overall SZ risk. Subgroup analysis also failed to show any significant association between all SNPs and the risk of SZ. Conclusion: In summary, this study revealed that the EGR3 rs1996147 AA genotype was associated with a borderline risk for SZ.

Representation of Race and Ethnicity in the Contemporary US Health Cohort All of Us Research Program

Importance

To address systemic disparities in biomedical research, the All of Us (AoU) Research Program was created to identify the root causes and consequences of health outcomes in the US. However, the extent of AoU's racial and ethnic diversity is unknown.

Objective

To quantify representation of key racial and ethnic groups in the accruing AoU nationwide health cohort and compare with their actual representation in the US.

Design, Setting, and Participants

This cohort study compared the AoU program from May 2017 to June 2022 for individuals 18 years and older with the Decennial Survey 2020 (DEC) collected by the US Census Bureau.

Exposures

Representation of non-Hispanic Asian, non-Hispanic Black or African American, Hispanic or Latino, non-Hispanic White, and uncategorized or multiple races in AoU.

Main Outcomes and Measures

The extent of underrepresentation or overrepresentation of each racial group in the AoU program at both nationwide and state-level relative to DEC.

Results

Of the 358 705 US adults in the AoU to date, individuals identified with the following race and ethnicity categories: 12 710 non-Hispanic Asian (3.5%), 73 348 non-Hispanic Black or African American (20.5%), 58 488 Hispanic or Latino (16.3%), 205 457 non-Hispanic White (57.3%), and 8702 uncategorized or reporting multiple categories (2.4%). Of 355 413 participants with available sex at birth and age data, 218 981 (61.6%) were female and had a mean (SD) age of 53.1 (17.0) years, 136 037 (38.28%) were male and had a mean (SD) age of 56.7 (17.0) years, and 395 reported nonbinary sex (0.1%), with a mean (SD) age of 55.4 (15.8) years. Compared with the referent US, non-Hispanic Black or African American individuals were overrepresented in the AoU by 8.73% (AoU, 20.5% [73 348 of 358 705] vs DEC, 11.7% [30 266 080 of 258 343 281]) and by relative scale, 1.94-fold. Non-Hispanic White individuals accounted for the greatest participation in the AoU with generally consistent dominance across all regions yet numerically underrepresented by absolute difference of -3.54% (95% CI, -3.70 to -3.38). Uncategorized or multiracial group in the AoU (2.4% [8702 of 358 705]) was 0.43-fold likely to be represented relative to the DEC (4.6% [11 922 096 of 258 343 281]) with an absolute difference of -2.19% (95% CI, -2.24 to -2.14). Moreover, non-Hispanic Asian individuals were underrepresented by -2.54% (95% CI, -2.60 to -2.48) prominently in most states. Individuals identifying as Hispanic or Latino were nominally underrepresented by -0.46% (95% CI, -0.58 to -0.34) (AoU, 16.3% [58 488 of 358 705] vs DEC, 16.8% [43 322 792 of 258 343 281]).

Conclusions and Relevance

Recruitment trends for the ongoing AoU show relatively improved representation of some major race groups with geographic trends. These findings underscore the need to further tailor and augment recruitment and participation initiatives for diverse populations.

Neurotransmitter Gene Polymorphisms Are Associated with Symptom Clusters in Patients Undergoing Radiation Therapy

OBJECTIVES

Purpose was to evaluate for associations between the severity of three distinct symptom clusters (ie, sickness-behavior, mood-cognitive, treatment-related) and polymorphisms for 16 genes involved in catecholaminergic, GABAergic, and serotonergic neurotransmission.

DATA SOURCES

Patients with breast and prostate cancer (n = 157) completed study questionnaires at the completion of radiation therapy. Memorial Symptom Assessment Scale was used to assess the severity of 32 common symptoms. Three distinct symptom clusters were identified using exploratory factor analysis. Associations between the symptom cluster severity scores and neurotransmitter gene polymorphisms were evaluated using regression analyses.

CONCLUSION

Severity scores for the sickness-behavior symptom cluster were associated with polymorphisms for solute carrier family 6 (SLC6A) member 2 (SLC6A2), SLC6A3, SLC6A1, and 5-hydroxytryptamine receptor (HTR) 2A (HTR2A) genes. For the mood-cognitive symptom cluster, severity scores were associated with polymorphisms for adrenoreceptor alpha 1D, SLC6A2, SLC6A3, SLC6A1, HTR2A, and HTR3A. Severity scores for the treatment-related symptom cluster were associated with polymorphisms for SLC6A2, SLC6A3, catechol-o-methyltransferase, SLC6A1, HTR2A, SLC6A4, and tryptophan hydroxylase 2.

IMPLICATIONS FOR NURSING PRACTICE

Findings suggest that polymorphisms for several neurotransmitter genes are involved in the severity of sickness-behavior, mood-cognitive, and treatment-related symptom clusters in oncology patients at the completion of radiation therapy. Four genes with various associated polymorphisms were common across the three distinct symptom clusters (ie, SLC6A2, SLC6A3, SLC6A1, HTR2A) which suggest that these clusters have common underlying mechanisms.

Genetic and epigenetic effects on couple adjustment in context of romantic relationship: A scoping systematic review

Introduction: Couples' relationships defined by a complex interaction between the two partners and their intrapersonal traits. Romantic; relationships and love are associated with marital satisfaction and stability, as well as couples' happiness and health. Personality traits influence romantic relationships and, personality influenced by genetical and non-genetically factors. The roles of non-genetically factors such as socioeconomic position and external appearance have revealed in determining the quality of romantic relationships. Methods: We; performed a scoping systematic review to assess the association between genetics and epigenetic factors and romantic relationship. Relevant articles were identified by PubMed, EMBASE, Web of Science, Scopus, and the APA PsycInfo searching between inception and 4 June 2022. Results: Different studies evaluated the associated polymorphisms in 15 different genes or chromosomal regions. In the first step; we classified them into four groups: (1) Oxytocin-related signaling pathway (OXTR, CD38, and AVPR1A); (2) Serotonin-related signaling pathway (SLC6A4, HTR1A, and HTR2A); (3) Dopamine and catecholamine-related signaling pathway (DRD1, DRD2, DRD4, ANKK1, and COMT); and (4) other genes (HLA, GABRA2, OPRM1, and Y-DNA haplogroup D-M55). Then, we evaluated and extracted significant polymorphisms that affect couple adjustment and romantic relationships. Discussion: Overall, the findings suggest that genetic and epigenetics variants play a key role in marital adjustment and romantic relationships over time.

Association of TYR SNP rs1042602 with Melanoma Risk and Prognosis

Cutaneous melanoma is the most aggressive of skin tumors. In order to discover new biomarkers that could help us improve prognostic prediction in melanoma patients, we have searched for germline DNA variants associated with melanoma progression. Thus, after exome sequencing of a set of melanoma patients and healthy control individuals, we identified rs1042602, an SNP within TYR, as a good candidate. After genotyping rs1042602 in 1025 patients and 773 healthy donors, we found that the rs1042602-A allele was significantly associated with susceptibility to melanoma (CATT test: p = 0.0035). Interestingly, we also observed significant differences between patients with good and bad prognosis (5 years of follow-up) (n = 664) (CATT test for all samples p = 0.0384 and for men alone p = 0.0054). Disease-free-survival (DFS) analyses also showed that patients with the A allele had shorter DFS periods. In men, the association remained significant even in a multivariate Cox Proportional-hazards model, which was adjusted for age at diagnosis, Breslow thickness, ulceration and melanoma subtype (HR 0.4; 95% confidence interval (CI) 0.20-0.83; p = 0.0139). Based on our results, we propose that rs1042602-A is a risk allele for melanoma, which also seems to be responsible for a poorer prognosis of the disease, particularly in men.

Gene Sequencing Identifies Perturbation in Nitric Oxide Signaling as a Nonlipid Molecular Subtype of Coronary Artery Disease

BACKGROUND

A key goal of precision medicine is to disaggregate common, complex diseases into discrete molecular subtypes. Rare coding variants in the low-density lipoprotein receptor gene (LDLR) are identified in 1% to 2% of coronary artery disease (CAD) patients, defining a molecular subtype with risk driven by hypercholesterolemia.

METHODS

To search for additional subtypes, we compared the frequency of rare, predicted loss-of-function and damaging missense variants aggregated within a given gene in 41 081 CAD cases versus 217 115 controls.

RESULTS

Rare variants in LDLR were most strongly associated with CAD, present in 1% of cases and associated with 4.4-fold increased CAD risk. A second subtype was characterized by variants in endothelial nitric oxide synthase gene (NOS3), a key enzyme regulating vascular tone, endothelial function, and platelet aggregation. A rare predicted loss-of-function or damaging missense variants in NOS3 was present in 0.6% of cases and associated with 2.42-fold increased risk of CAD (95% CI, 1.80-3.26; P=5.50×10-9). These variants were associated with higher systolic blood pressure (+3.25 mm Hg; [95% CI, 1.86-4.65]; P=5.00×10-6) and increased risk of hypertension (adjusted odds ratio 1.31; [95% CI, 1.14-1.51]; P=2.00×10-4) but not circulating cholesterol concentrations, suggesting that, beyond lipid pathways, nitric oxide synthesis is a key nonlipid driver of CAD risk.

CONCLUSIONS

Beyond LDLR, we identified an additional nonlipid molecular subtype of CAD characterized by rare variants in the NOS3 gene.

Age structuring and spatial heterogeneity in prion protein gene (PRNP) polymorphism in white-tailed deer

Chronic-wasting disease (CWD) is a prion-derived fatal neurodegenerative disease that has affected wild cervid populations on a global scale. Susceptibility has been linked unambiguously to several amino acid variants within the prion protein gene (PRNP). Quantifying their distribution across landscapes can provide critical information for agencies attempting to adaptively manage CWD. Here we attempt to further define management implications of PRNP polymorphism by quantifying the contemporary geographic distribution (i.e., phylogeography) of PRNP variants in hunter-harvested white-tailed deer (WTD; Odocoileus virginianus, N = 1433) distributed across Arkansas (USA), including a focal spot for CWD since detection of the disease in February 2016. Of these, PRNP variants associated with the well-characterized 96S non-synonymous substitution showed a significant increase in relative frequency among older CWD-positive cohorts. We interpreted this pattern as reflective of a longer life expectancy for 96S genotypes in a CWD-endemic region, suggesting either decreased probabilities of infection or reduced disease progression. Other variants showing statistical signatures of potential increased susceptibility, however, seemingly reflect an artefact of population structure. We also showed marked heterogeneity across the landscape in the prevalence of ‘reduced susceptibility’ genotypes. This may indicate, in turn, that differences in disease susceptibility among WTD in Arkansas are an innate, population-level characteristic that is detectable through phylogeographic analysis.

Genetic Ancestry Inference and Its Application for the Genetic Mapping of Human Diseases

Admixed populations arise when two or more ancestral populations interbreed. As a result of this admixture, the genome of admixed populations is defined by tracts of variable size inherited from these parental groups and has particular genetic features that provide valuable information about their demographic history. Diverse methods can be used to derive the ancestry apportionment of admixed individuals, and such inferences can be leveraged for the discovery of genetic loci associated with diseases and traits, therefore having important biomedical implications. In this review article, we summarize the most common methods of global and local genetic ancestry estimation and discuss the use of admixture mapping studies in human diseases.

Identification of ancestry proportions in admixed groups across the Americas using clinical pharmacogenomic SNP panels

We evaluated the performance of three PGx panels to estimate biogeographical ancestry: the DMET panel, and the VIP and Preemptive PGx panels described in the literature. Our analysis indicate that the three panels capture quite well the individual variation in admixture proportions observed in recently admixed populations throughout the Americas, with the Preemptive PGx and DMET panels performing better than the VIP panel. We show that these panels provide reliable information about biogeographic ancestry and can be used to guide the implementation of PGx clinical decision-support (CDS) tools. We also report that using these panels it is possible to control for the effects of population stratification in association studies in recently admixed populations, as exemplified with a warfarin dosing GWA study in a sample from Brazil.

The KLF14 Variant is Associated with Type 2 Diabetes and HbA1C Level

The purpose of this study was to scan variants in coding region of Krȕppel like factor14 (KLF14) locus and assess association related to type 2 diabetes (T2D) in Iranian population. We sequenced the coding region of KLF14 to scan variants in case-sibling study (92 individuals with T2D and 92 healthy older siblings). To confirm, we analyzed rs76603546 association with T2D in a larger unrelated case-control study by PCR-RFLP (475 cases and 512 controls). We analyzed the association of rs76603546 with HbA_1C, BMI, fat mass, waist circumference, fasting glucose, cholesterol and HOMA-IR (Homeostatic Model Assessment for Insulin Resistance) using one-way ANOVA analysis. Also, association of genotypes with T2D adjusted for confounding variables was analyzed using logistic regression. HaploReg v 4.1 was used to predict rs76603546 possible function. Sequencing results analysis revealed the association of C allele of rs76603546, synonymous variant C>T, [OR 2.10 (1.38-3.20), P value < 0.001] and CC genotype of rs76603546 [OR 4.3 (1.79-10.23), P value = 0.001] with susceptibility to T2D. PCR-Restriction Fragment Length Polymorphism (RFLP) results analysis confirmed the association of rs76603546 with T2D [C allele, OR 1.91 (1.59-2.29), P value = 0.002, CC genotype, OR 3.27 (2.26-4.73), P value = 0.002 and TC genotype, OR 1.74 (1.31-2.31), P value = 0.001]. The CC genotype of rs76603546 is associated with HbA_1C level (P value < 0.001) and BMI (P value = 0.02). After adjustment with confounding variables, we observed association of CC genotype with T2D [OR 2.542 (1.25-3.77), P value = 0.03]. Among over 220 SNPs, rs76603546 was associated with T2D, HbA_1C and BMI in our study.

Association of variants in IL1B, TLR9, TREM1, IL10RA, and CD3G and Native American ancestry on malaria susceptibility in Colombian populations

Host genetics is an influencing factor in the manifestation of infectious diseases. In this study, the association of mild malaria with 28 variants in 16 genes previously reported in other populations and/or close to ancestry-informative markers (AIMs) selected was evaluated in an admixed 736 Colombian population sample. Additionally, the effect of genetic ancestry on phenotype expression was explored. For this purpose, the ancestral genetic composition of Turbo and El Bagre was determined. A higher Native American ancestry trend was found in the population with lower malaria susceptibility [odds ratio (OR) = 0.416, 95% confidence interval (95% CI) = 0.234-0.740, P = 0.003]. Three AIMs presented significant associations with the disease phenotype (MID1752, MID921, and MID1586). The first two were associated with greater malaria susceptibility (D/D, OR = 2.23, 95% CI = 1.06-4.69, P = 0.032 and I/D-I/I, OR = 2.14, 95% CI = 1.18-3.87, P = 0.011, respectively), and the latter has a protective effect on the appearance of malaria (I/I, OR = 0.18, 95% CI = 0.08-0.40, P < 0.0001). After adjustment by age, sex, municipality, and genetic ancestry, genotype association analysis showed evidence of association with malaria susceptibility for variants in or near IL1B, TLR9, TREM1, IL10RA, and CD3G genes: rs1143629-IL1B (G/A-A/A, OR = 0.41, 95% CI = 0.21-0.78, P = 0.0051), rs352139-TLR9 (T/T, OR = 0.28, 95% CI = 0.11-0.72, P = 0.0053), rs352140-TLR9 (C/C, OR = 0.41, 95% CI = 0.20-0.87, P = 0.019), rs2234237-TREM1 (T/A-A/A, OR = 0.43, 95% CI = 0.23-0.79, P = 0.0056), rs4252246-IL10RA (C/A-A/A, OR = 2.11, 95% CI = 1.18-3.75, P = 0.01), and rs1561966-CD3G (A/A, OR = 0.20, 95% CI = 0.06-0.69, P = 0.0058). The results showed the participation of genes involved in immunological processes and suggested an effect of ancestral genetic composition over the traits analyzed. Compared to the paisa population (Antioquia), Turbo and El Bagre showed a strong decrease in European ancestry and an increase in African and Native American ancestries. Also, a novel association of two single nucleotide polymorphisms with malaria susceptibility was identified in this study.

The Impact of African Ancestry on Prostate Cancer Disparities in the Era of Precision Medicine

Prostate cancer disproportionately affects men of African ancestry at nearly twice the rate of men of European ancestry despite the advancement of treatment strategies and prevention. In this review, we discuss the underlying causes of these disparities including genetics, environmental/behavioral, and social determinants of health while highlighting the implications and challenges that contribute to the stark underrepresentation of men of African ancestry in clinical trials and genetic research studies. Reducing prostate cancer disparities through the development of personalized medicine approaches based on genetics will require a holistic understanding of the complex interplay of non-genetic factors that disproportionately exacerbate the observed disparity between men of African and European ancestries.

Sleep disruption and duration are associated with variants in genes involved in energy homeostasis in adults with HIV/AIDS

OBJECTIVE

To determine whether selected genes and plasma markers involved in energy homeostasis are associated with sleep disruption or duration in adults with HIV/AIDS.

METHODS

A sample of 289 adults with HIV/AIDS wore a wrist actigraph for 72 h to estimate total sleep time (TST) and wake after sleep onset (WASO). Twenty-three single nucleotide polymorphisms (SNP) spanning 5 energy homeostasis genes (adiponectin [ADIPOQ], ghrelin [GHRL], leptin [LEP], peroxisome proliferator-activated receptor-alpha [PPARA], and -gamma [PPARG]) were genotyped using a custom array. Plasma markers of energy homeostasis (adiponectin, ghrelin, leptin) were measured by commercial multiplex assay.

RESULTS

After adjusting for demographic and clinical characteristics (race/ethnicity, gender, CD4 cell count, waist circumference, medications), both WASO and TST were associated with SNPs in ADIPOQ (rs182052), LEP (rs10244329, rs3828942), PPARA (rs135551, rs4253655), and PPARG (rs709151). Additional SNPs in ADIPOQ were associated with WASO (rs1501299, rs3821799, rs6773957) and TST (rs2241766). TST was also associated with SNPs in GHRL (rs26802), LEP (rs11760956), PPARA (rs135547, rs8138102, rs4253776), and PPARG (rs12490265, rs796313). Many covariate-adjusted associations involved a significant interaction with markers of HIV (viral load, years since diagnosis). Among plasma markers, higher adiponectin was associated with less WASO, higher ghrelin and glucose levels with shorter TST, and higher leptin with longer TST.

CONCLUSIONS

Replication of SNPs in all five genes and three plasma markers of energy homeostasis were associated with objective sleep measures. HIV disease influenced many of the associations. Findings strengthen evidence for associations between energy homeostasis genetics and poor sleep, and provide direction for pharmacological intervention research.

The Advantages and Challenges of Diversity in Pharmacogenomics: Can Minority Populations Bring Us Closer to Implementation?

Health disparities exist among minorities in the United States, with differences seen in disease prevalence, mortality, and responses to medications. These differences are multifactorial with genetic variation explaining a portion of this variability. Pharmacogenomics aims to find the effect of genetic variations on drug response, with the goal of optimizing drug therapy and development. Although genome-wide association studies have been useful in unbiasedly surveying the genome for genetic drivers of clinically relevant phenotypes, most of these studies have been conducted in mainly participants of European and Asian descent, contributing to a growing health disparity in precision medicine. Diversity is important to pharmacogenomic studies, and there may be real advantages to the use of these complex genomes in pharmacogenomics. In this review we will outline some of the advantages and confounders of pharmacogenomics in minorities, describe the role of genetic variation in pharmacologic pathways, and highlight a number of population-specific findings.

Genetic Association of Finger Photoplethysmography-Derived Arterial Stiffness Index With Blood Pressure and Coronary Artery Disease

Objective- Arterial stiffness index (ASI) is independently associated with blood pressure (BP) and coronary artery disease (CAD) epidemiologically. However, it is unknown whether these associations represent causal relationships. Here, we assess whether genetic predisposition to increased ASI is associated with elevated BP and CAD risk. Approach and Results- We first performed a large-scale epidemiological association of finger photoplethysmography-derived ASI in the UK Biobank, finding significant associations with systolic BP (β=0.55 mm Hg; [95% CI, 0.45-0.65]; P=5.77×10^-24; N=137 858), diastolic BP (β=1.05 mm Hg; [95% CI, 0.99-1.11]; P=7.27×10^-272; N=137 862), and incident CAD (hazard ratio, 1.08; [95% CI, 1.04-1.11]; P=1.5×10^-6; N=3692 cases, 126 615 controls) in multivariable models. We then performed an ASI genome-wide association study analysis in 131 686 participants from the UK Biobank. Across participants not in the ASI genome-wide association study, a 6-variant ASI polygenic risk score was calculated. Each SD increase in genetic ASI was associated with systolic BP (β=4.63 mm Hg; [95% CI, 2.1-7.2]; P=3.37×10^-4; N=208 897), and diastolic BP (β=2.61 mm Hg; [95% CI, 1.2-4.0]; P=2.85×10^-4; N=208 897); however, no association was observed with incident CAD (hazard ratio, 1.12; [95% CI, 0.55-2.3]; P=0.75; N=223 061; 7534 cases). The lack of CAD association observed was replicated among 184 305 participants (60 810 cases) from the CARDIOGRAMplusC4D (Coronary Artery Disease Genetics Consortium; odds ratio, 0.56; [95% CI, 0.26-1.24]; P=0.15). Conclusions- Our data support the conclusion that finger photoplethysmography-derived ASI is an independent, genetically causal risk factor for BP, but do not support the notion that ASI is a suitable surrogate for CAD risk.

The quandary of covarying: A brief review and empirical examination of covariate use in structural neuroimaging studies on psychological variables

Although covarying for potential confounds or nuisance variables is common in psychological research, relatively little is known about how the inclusion of covariates may influence the relations between psychological variables and indices of brain structure. In Part 1 of the current study, we conducted a descriptive review of relevant articles from the past two years of NeuroImage in order to identify the most commonly used covariates in work of this nature. Age, sex, and intracranial volume were found to be the most commonly used covariates, although the number of covariates used ranged from 0 to 14, with 37 different covariate sets across the 68 models tested. In Part 2, we used data from the Human Connectome Project to investigate the degree to which the addition of common covariates altered the relations between individual difference variables (i.e., personality traits, psychopathology, cognitive tasks) and regional gray matter volume (GMV), as well as the statistical significance of values associated with these effect sizes. Using traditional and random sampling approaches, our results varied widely, such that some covariate sets influenced the relations between the individual difference variables and GMV very little, while the addition of other covariate sets resulted in a substantially different pattern of results compared to models with no covariates. In sum, these results suggest that the use of covariates should be critically examined and discussed as part of the conversation on replicability in structural neuroimaging. We conclude by recommending that researchers pre-register their analytic strategy and present information on how relations differ based on the inclusion of covariates.

Associations Between Catecholaminergic and Serotonergic Genes and Persistent Arm Pain Severity Following Breast Cancer Surgery

Persistent arm pain is a common problem after breast cancer surgery. Little is known about genetic factors that contribute to this type of postsurgical pain. Study purpose was to explore associations between persistent arm pain phenotypes and genetic polymorphisms among 15 genes involved in catecholaminergic and serotonergic neurotransmission. Women (n = 398) rated the presence and intensity of arm pain monthly for 6 months after breast cancer surgery. Three distinct latent classes of patients were identified (ie, no arm pain [41.6%], mild arm pain (23.6%), and moderate arm pain (34.8%). Logistic regression analyses were used to evaluate for differences between genotype or haplotype frequencies and the persistent arm pain classes. Compared with the no arm pain class, 3 single nucleotide polymorphisms and 1 haplotype, in 4 genes, were associated with membership in the mild arm pain class: COMT rs4633, HTR2A haplotype B02 (composed of rs1923886 and rs7330636), HTR3A rs1985242, and TH rs2070762. Compared with the no arm pain class, 4 single nucleotide polymorphisms in 3 genes were associated with membership in the moderate arm pain class: COMT rs165656, HTR2A rs2770298 and rs9534511, and HTR3A rs1985242. Findings suggest that variations in catecholaminergic and serotonergic genes play a role in the development of persistent arm pain. PERSPECTIVE: Limited information is available on genetic factors that contribute to persistent arm pain after breast cancer surgery. Genetic polymorphisms in genes involved in catecholaminergic and serotonergic neurotransmission were associated with 2 persistent arm pain phenotypes. Findings may be used to identify patients are higher risk for this common pain condition.

A systematic literature review on the European, African and Amerindian genetic ancestry components on Brazilian health outcomes

The variables such as race, skin colour and ethnicity have become intensely discussed in medicine research, as a response to the rising debate over the importance of the ethnic-racial dimension in the scope of health-disease processes. The aim of this study was to identify the European (EUR), African (AFR) and Amerindian (AMR) ancestries on Brazilian health outcomes through a systematic literature review. This study was carried out by searching in three electronic databases, for studies published between 2005 and 2017. A total of 13 papers were eligible. The search identified the following health outcomes: visceral leishmaniosis, malaria, Alzheimer’s disease, neuromyelitis optica, multiple sclerosis, prostate cancer, non-syndromic cleft lip/palate, chronic heart failure, sickle cell disease, primary congenital glaucoma, preterm labour, preterm premature rupture of membranes, systemic lupus erythematosus and type 1 diabetes mellitus. Research paper assessments were guided by the STROBE instrument, and agreements between results were determined by comparing the points attributed by two authors. Increased EUR ancestry was identified from preterm labour (PTL), type 1 diabetes (T1D) and non-syndromic cleft lip with or without cleft palate (NSCL), as well as in patients presenting aggressive prostate cancer prognoses. On the other hand, the highest AFR ancestral component was verified from systemic lupus erythematosus (SLE) and primary congenital glaucoma (PCG) cases, presenting worse prognoses. AMR ancestry may be a protective factor in the development of Alzheimer’s disease (AD). The worst hemodynamic parameters in cases of heart failure (HF) were identified among individuals with greater AMR and AFR ancestry indices.

Shades of complexity: New perspectives on the evolution and genetic architecture of human skin

Like many highly variable human traits, more than a dozen genes are known to contribute to the full range of skin color. However, the historical bias in favor of genetic studies in European and European-derived populations has blinded us to the magnitude of pigmentation's complexity. As deliberate efforts are being made to better characterize diverse global populations and new sequencing technologies, better measurement tools, functional assessments, predictive modeling, and ancient DNA analyses become more widely accessible, we are beginning to appreciate how limited our understanding of the genetic bases of human skin color have been. Novel variants in genes not previously linked to pigmentation have been identified and evidence is mounting that there are hundreds more variants yet to be found. Even for genes that have been exhaustively characterized in European populations like MC1R, OCA2, and SLC24A5, research in previously understudied groups is leading to a new appreciation of the degree to which genetic diversity, epistatic interactions, pleiotropy, admixture, global and local adaptation, and cultural practices operate in population-specific ways to shape the genetic architecture of skin color. Furthermore, we are coming to terms with how factors like tanning response and barrier function may also have influenced selection on skin throughout human history. By examining how our knowledge of pigmentation genetics has shifted in the last decade, we can better appreciate how far we have come in understanding human diversity and the still long road ahead for understanding many complex human traits.

An Ancestry Informative Marker Set Which Recapitulates the Known Fine Structure of Populations in South Asia

The inference of genomic ancestry using ancestry informative markers (AIMs) can be useful for a range of studies in evolutionary genetics, biomedical research, and forensic analyses. However, the determination of AIMs for highly admixed populations with complex ancestries has remained a formidable challenge. Given the immense genetic heterogeneity and unique population structure of the Indian subcontinent, here we sought to derive AIMs that would yield a cohesive and faithful understanding of South Asian genetic origins. To discern the most optimal strategy for extracting AIMs for South Asians we compared three commonly used AIMs-determining methods namely, Infocalc, FST, and Smart Principal Component Analysis with ADMIXTURE, using previously published whole genome data from the Indian subcontinent. Our findings suggest that the Infocalc approach is likely most suitable for delineation of South Asian AIMs. In particular, Infocalc-2,000 (N = 2,000) appeared as the most informative South Asian AIMs panel that recapitulated the finer structure within South Asian genomes with high degree of sensitivity and precision, whereas a negative control with an equivalent number of randomly selected markers when used to interrogate the South Asian populations, failed to do so. We discuss the utility of all approaches under evaluation for AIMs derivation and interpreting South Asian genomic ancestries. Notably, this is the first report of an AIMs panel for South Asian ancestry inference. Overall these findings may aid in developing cost-effective resources for large-scale demographic analyses and foster expansion of our knowledge of human origins and disease, in the South Asian context.

Deep coverage whole genome sequences and plasma lipoprotein(a) in individuals of European and African ancestries

Lipoprotein(a), Lp(a), is a modified low-density lipoprotein particle that contains apolipoprotein(a), encoded by LPA, and is a highly heritable, causal risk factor for cardiovascular diseases that varies in concentrations across ancestries. Here, we use deep-coverage whole genome sequencing in 8392 individuals of European and African ancestry to discover and interpret both single-nucleotide variants and copy number (CN) variation associated with Lp(a). We observe that genetic determinants between Europeans and Africans have several unique determinants. The common variant rs12740374 associated with Lp(a) cholesterol is an eQTL for SORT1 and independent of LDL cholesterol. Observed associations of aggregates of rare non-coding variants are largely explained by LPA structural variation, namely the LPA kringle IV 2 (KIV2)-CN. Finally, we find that LPA risk genotypes confer greater relative risk for incident atherosclerotic cardiovascular diseases compared to directly measured Lp(a), and are significantly associated with measures of subclinical atherosclerosis in African Americans.

A plausibly causal functional lupus-associated risk variant in the STAT1-STAT4 locus

Systemic lupus erythematosus (SLE or lupus) (OMIM: 152700) is a chronic autoimmune disease with debilitating inflammation that affects multiple organ systems. The STAT1-STAT4 locus is one of the first and most highly replicated genetic loci associated with lupus risk. We performed a fine-mapping study to identify plausible causal variants within the STAT1-STAT4 locus associated with increased lupus disease risk. Using complementary frequentist and Bayesian approaches in trans-ancestral Discovery and Replication cohorts, we found one variant whose association with lupus risk is supported across ancestries in both the Discovery and Replication cohorts: rs11889341. In B cell lines from patients with lupus and healthy controls, the lupus risk allele of rs11889341 was associated with increased STAT1 expression. We demonstrated that the transcription factor HMGA1, a member of the HMG transcription factor family with an AT-hook DNA-binding domain, has enriched binding to the risk allele compared with the non-risk allele of rs11889341. We identified a genotype-dependent repressive element in the DNA within the intron of STAT4 surrounding rs11889341. Consistent with expression quantitative trait locus (eQTL) analysis, the lupus risk allele of rs11889341 decreased the activity of this putative repressor. Altogether, we present a plausible molecular mechanism for increased lupus risk at the STAT1-STAT4 locus in which the risk allele of rs11889341, the most probable causal variant, leads to elevated STAT1 expression in B cells due to decreased repressor activity mediated by increased binding of HMGA1.

Genome-wide mapping of quantitative trait loci in admixed populations using mixed linear model and Bayesian multiple regression analysis

Background

Population stratification and cryptic relationships have been the main sources of excessive false-positives and false-negatives in population-based association studies. Many methods have been developed to model these confounding factors and minimize their impact on the results of genome-wide association studies. In most of these methods, a two-stage approach is applied where: (1) methods are used to determine if there is a population structure in the sample dataset and (2) the effects of population structure are corrected either by modeling it or by running a separate analysis within each sub-population. The objective of this study was to evaluate the impact of population structure on the accuracy and power of genome-wide association studies using a Bayesian multiple regression method.

Methods

We conducted a genome-wide association study in a stochastically simulated admixed population. The genome was composed of six chromosomes, each with 1000 markers. Fifteen segregating quantitative trait loci contributed to the genetic variation of a quantitative trait with heritability of 0.30. The impact of genetic relationships and breed composition (BC) on three analysis methods were evaluated: single marker simple regression (SMR), single marker mixed linear model (MLM) and Bayesian multiple-regression analysis (BMR). Each method was fitted with and without BC. Accuracy, power, false-positive rate and the positive predictive value of each method were calculated and used for comparison.

Results

SMR and BMR, both without BC, were ranked as the worst and the best performing approaches, respectively. Our results showed that, while explicit modeling of genetic relationships and BC is essential for models SMR and MLM, BMR can disregard them and yet result in a higher power without compromising its false-positive rate.

Conclusions

This study showed that the Bayesian multiple-regression analysis is robust to population structure and to relationships among study subjects and performs better than a single marker mixed linear model approach.

Nonparametric approaches for population structure analysis

The analysis of population structure has many applications in medical and population genetic research. Such analysis is used to provide clear insight into the underlying genetic population substructure and is a crucial prerequisite for any analysis of genetic data. The analysis involves grouping individuals into subpopulations based on shared genetic variations. The most widely used markers to study the variation of DNA sequences between populations are single nucleotide polymorphisms. Data preprocessing is a necessary step to assess the quality of the data and to determine which markers or individuals can reasonably be included in the analysis. After preprocessing, several methods can be utilized to uncover population substructure, which can be categorized into two broad approaches: parametric and nonparametric. Parametric approaches use statistical models to infer population structure and assign individuals into subpopulations. However, these approaches suffer from many drawbacks that make them impractical for large datasets. In contrast, nonparametric approaches do not suffer from these drawbacks, making them more viable than parametric approaches for analyzing large datasets. Consequently, nonparametric approaches are increasingly used to reveal population substructure. Thus, this paper reviews and discusses the nonparametric approaches that are available for population structure analysis along with some implications to resolve challenges.

Cytokine Gene Polymorphisms Associated With Various Domains of Quality of Life in Women With Breast Cancer

CONTEXT

Little is known about the phenotypic and molecular characteristics associated with various domains of quality of life (QOL) in women after breast cancer surgery.

OBJECTIVES

In a sample of women with breast cancer (n = 398), purposes were as follows: to identify latent classes with distinct trajectories of QOL from before surgery through six months after surgery and to evaluate for differences in demographic and clinical characteristics, as well as for polymorphisms in cytokine genes, between these latent classes.

METHODS

Latent class analyses were done to identify subgroups of patients with distinct QOL outcomes. Candidate gene analyses were done to identify cytokine gene polymorphisms associated with various domains of QOL (i.e., physical, psychological, spiritual, social).

RESULTS

One latent class was identified for the psychological and spiritual domains. Two latent classes were identified for the social domain and overall QOL scores. Three latent classes were identified for the physical domain. For the physical and social domains, as well as for the overall QOL scores, distinct phenotypic characteristics (i.e., younger age, poorer functional status, higher body mass index, and receipt of adjuvant chemotherapy) and a number of cytokine gene polymorphisms (CXCL8, NFKB2, TNFSF, IL1B, IL13, and NFKB1) were associated with membership in the lower QOL classes.

CONCLUSIONS

Findings suggest that women experience distinctly different physical well-being, social well-being, and total QOL outcomes during and after breast cancer surgery. The genetic associations identified suggest that cytokine dysregulation influences QOL outcomes. However, specific QOL domains may be impacted by different cytokines.

Admixture mapping of uterine fibroid size and number in African American women

OBJECTIVE

To evaluate the relationship between genetic ancestry and uterine fibroid characteristics.

DESIGN

Cross-sectional study.

SETTING

Not applicable.

PATIENT(S)

A total of 609 African American participants with image- or surgery-confirmed fibroids in a biorepository at Vanderbilt University electronic health record biorepository and the Coronary Artery Risk Development in Young Adults studies were included.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

Outcome measures include fibroid number (single vs. multiple), volume of largest fibroid, and largest fibroid dimension of all fibroid measurements.

RESULT(S)

Global ancestry meta-analyses revealed a significant inverse association between percentage of European ancestry and risk of multiple fibroids (odds ratio: 0.78; 95% confidence interval 0.66, 0.93; P=6.05 × 10-3). Local ancestry meta-analyses revealed five suggestive (P<4.80 × 10-3) admixture mapping peaks in 2q14.3-2q21.1, 3p14.2-3p14.1, 7q32.2-7q33, 10q21.1, 14q24.2-14q24.3, for number of fibroids and one suggestive admixture mapping peak (P<1.97 × 10-3) in 10q24.1-10q24.32 for volume of largest fibroid. Single variant association meta-analyses of the strongest associated region from admixture mapping of fibroid number (10q21.1) revealed a strong association at single nucleotide polymorphism variant rs12219990 (odds ratio: 0.41; 95% confidence interval 0.28, 0.60; P=3.82 × 10-6) that was significant after correction for multiple testing.

CONCLUSION(S)

Increasing African ancestry is associated with multiple fibroids but not with fibroid size. Local ancestry analyses identified several novel genomic regions not previously associated with fibroid number and increasing volume. Future studies are needed to explore the genetic impact that ancestry plays into the development of fibroid characteristics.

Population Stratification in Genetic Association Studies

Population stratification (PS) is a primary consideration in studies of genetic determinants of human traits. Failure to control for PS may lead to confounding, causing a study to fail for lack of significant results, or resources to be wasted following false-positive signals. Here, historical and current approaches for addressing PS when performing genetic association studies in human populations are reviewed. Methods for detecting the presence of PS, including global and local ancestry methods, are described. Also described are approaches for accounting for PS when calculating association statistics, such that measures of association are not confounded. Many traits are being examined for the first time in minority populations, which may inherently feature PS. © 2017 by John Wiley & Sons, Inc.

Genome-wide association study of sepsis in extremely premature infants

OBJECTIVE

To identify genetic variants associated with sepsis (early-onset and late-onset) using a genome-wide association (GWA) analysis in a cohort of extremely premature infants.

STUDY DESIGN

Previously generated GWA data from the Neonatal Research Network's anonymised genomic database biorepository of extremely premature infants were used for this study. Sepsis was defined as culture-positive early-onset or late-onset sepsis or culture-proven meningitis. Genomic and whole-genome-amplified DNA was genotyped for 1.2 million single-nucleotide polymorphisms (SNPs); 91% of SNPs were successfully genotyped. We imputed 7.2 million additional SNPs. p Values and false discovery rates (FDRs) were calculated from multivariate logistic regression analysis adjusting for gender, gestational age and ancestry. Target statistical value was p<10-5. Secondary analyses assessed associations of SNPs with pathogen type. Pathway analyses were also run on primary and secondary end points.

RESULTS

Data from 757 extremely premature infants were included: 351 infants with sepsis and 406 infants without sepsis. No SNPs reached genome-wide significance levels (5×10-8); two SNPs in proximity to FOXC2 and FOXL1 genes achieved target levels of significance. In secondary analyses, SNPs for ELMO1, IRAK2 (Gram-positive sepsis), RALA, IMMP2L (Gram-negative sepsis) and PIEZO2 (fungal sepsis) met target significance levels. Pathways associated with sepsis and Gram-negative sepsis included gap junctions, fibroblast growth factor receptors, regulators of cell division and interleukin-1-associated receptor kinase 2 (p values<0.001 and FDR<20%).

CONCLUSIONS

No SNPs met genome-wide significance in this cohort of extremely low birthweight infants; however, areas of potential association and pathways meriting further study were identified.

Cytokine Gene Polymorphisms Associated With Symptom Clusters in Oncology Patients Undergoing Radiation Therapy

CONTEXT

Most of the reviews on the biological basis for symptom clusters suggest that inflammatory processes are involved in the development and maintenance of the symptom clusters. However, no studies have evaluated for associations between genetic polymorphisms and common symptom clusters (e.g., mood disturbance, sickness behavior).

OBJECTIVES

Examine the associations between cytokine gene polymorphisms and the severity of three distinct symptom clusters (i.e., mood-cognitive, sickness-behavior, treatment-related) in a sample of patients with breast and prostate cancer (n = 157) at the completion of radiation therapy.

METHODS

Symptom severity was assessed using the Memorial Symptom Assessment Scale. Symptom clusters were created using exploratory factor analysis. The associations between cytokine gene polymorphisms and the symptom cluster severity scores were evaluated using regression analyses.

RESULTS

Polymorphisms in C-X-C motif chemokine ligand 8 (CXCL8), interleukin (IL13), and nuclear factor kappa beta 2 (NFKB2) were associated with severity scores for the mood-cognitive symptom cluster. In addition to interferon gamma (IFNG1), the same polymorphism in NFKB2 (i.e., rs1056890) that was associated with the mood-cognitive symptom cluster score was associated with the sickness-behavior symptom cluster. Polymorphisms in interleukin 1 receptor 1 (IL1R1), IL6, and NFKB1 were associated with severity factor scores for the treatment-related symptom cluster.

CONCLUSION

Our findings support the hypotheses that symptoms that cluster together have a common underlying mechanism and the most common symptom clusters in oncology patients are associated polymorphisms in genes involved in a variety of inflammatory processes.

Associations between genetic and epigenetic variations in cytokine genes and mild persistent breast pain in women following breast cancer surgery

Persistent pain following breast cancer surgery is a significant problem. Both inherited and acquired mechanisms of inflammation appear to play a role in the development and maintenance of persistent pain. In this longitudinal study, growth mixture modeling was used to identify persistent breast pain phenotypes based on pain assessments obtained prior to and monthly for 6months following breast cancer surgery. Associations between the "no pain" and "mild pain" phenotypes and single nucleotide polymorphisms (SNPs) spanning 15 cytokine genes were evaluated. The methylation status of the CpG sites found in the promoters of genes associated with pain group membership was determined using bisulfite sequencing. In the multivariate analysis, three SNPs (i.e., interleukin 6 (IL6) rs2069840, C-X-C motif chemokine ligand 8 (CXCL8) rs4073, tumor necrosis factor (TNF) rs1800610) and two TNF CpG sites (i.e., c.-350C, c.-344C) were associated with pain group membership. These findings suggest that variations in IL6, CXCL8, and TNF are associated with the development and maintenance of mild persistent breast pain. CpG methylation within the TNF promoter may provide an additional mechanism through which TNF alters the risk for mild persistent breast pain after breast cancer surgery. These genetic and epigenetic variations may help to identify individuals who are predisposed to the development of mild levels of persistent breast pain following breast cancer surgery.

Potassium Channel Candidate Genes Predict the Development of Secondary Lymphedema Following Breast Cancer Surgery

BACKGROUND

Potassium (K) channels play an important role in lymph pump activity, lymph formation, lymph transport, and the functions of lymph nodes. No studies have examined the relationship between K channel candidate genes and the development of secondary lymphedema (LE).

OBJECTIVE

The study purpose was to evaluate for differences in genotypic characteristics in women who did (n = 155) or did not (n = 387) develop upper extremity LE following breast cancer treatment based on an analysis of single-nucleotide polymorphisms (SNPs) and haplotypes in 10 K channel genes.

METHODS

Upper extremity LE was diagnosed using bioimpedance resistance ratios. Logistic regression analyses were used to identify those SNPs and haplotypes that were associated with LE while controlling for relevant demographic, clinical, and genomic characteristics.

RESULTS

Patients with LE had a higher body mass index, had a higher number of lymph nodes removed, had more advanced disease, received adjuvant chemotherapy, received radiation therapy, and were less likely to have undergone a sentinel lymph node biopsy. One SNP in a voltage-gated K channel gene (KCNA1 rs4766311), four in two inward-rectifying K channel genes (KCNJ3 rs1037091 and KCNJ6 rs2211845, rs991985, rs2836019), and one in a two-pore K channel gene (KCNK3 rs1662988) were associated with LE.

DISCUSSION

These preliminary findings suggest that K channel genes play a role in the development of secondary LE.

Genetic alterations in necrotizing enterocolitis

An underlying genetic predisposition to necrotizing enterocolitis (NEC) is increasingly being recognized. Candidate gene or pathway approaches as well as genome-wide approaches are beginning to identify potential pathogenic variants for NEC in premature infants. However, a majority of these studies have not yielded definitive results because of limited sample size and lack of validation. Despite these challenges, understanding the contribution of genetic variation to NEC is important for providing new insights into the pathogenesis of NEC as well as allowing for targeted care of infants with inherent susceptibility. In this review we provide a summary of published genetic association studies in NEC along with defining the challenges and possible future approaches.

The interaction between the dopamine receptor D4 (DRD4) variable number tandem repeat polymorphism and perceived peer drinking norms in adolescent alcohol use and misuse

Peer drinking norms are arguably one of the strongest correlates of adolescent drinking. Prospective studies indicate that adolescents tend to select peers based on drinking (peer selection) and their peers' drinking is associated with changes in adolescent drinking over time (peer socialization). The present study investigated whether the peer selection and socialization processes in adolescent drinking differed as a function of the dopamine receptor D4 (DRD4) variable number tandem repeat genotype in two independent prospective data sets. The first sample was 174 high school students drawn from a two-wave 6-month prospective study. The second sample was 237 college students drawn from a three-wave annual prospective study. Multigroup cross-lagged panel analyses of the high school student sample indicated stronger socialization via peer drinking norms among carriers, whereas analyses of the college student sample indicated stronger drinking-based peer selection in the junior year among carriers, compared to noncarriers. Although replication and meta-analytic synthesis are needed, these findings suggest that in part genetically determined peer selection (carriers of the DRD4 seven-repeat allele tend to associate with peers who have more favorable attitudes toward drinking and greater alcohol use) and peer socialization (carriers' subsequent drinking behaviors are more strongly associated with their peer drinking norms) may differ across adolescent developmental stages.

Cytokine polymorphisms are associated with daytime napping in adults living with HIV

OBJECTIVE/BACKGROUND

Daytime napping longer than one hour has been associated with an increased risk for all-cause mortality. Associations between cytokine polymorphisms and daytime napping in chronic illnesses such as HIV, however, have not been well described. The purpose of this study was to examine cytokine polymorphisms associated with long daytime napping in adults living with HIV.

METHODS

A cross-sectional analysis was conducted using a convenience sample of 257 adults living with HIV. Daytime napping was assessed with wrist actigraphy data collected over three days. Participants categorized as long nappers (≥60 min) were compared to short nappers and non-nappers (<60 min). Single nucleotide polymorphisms (SNPs) for 15 candidate genes involved in cytokine signaling were analyzed. Genes included: interferon-gamma (IFNG), IFNG receptor 1 (IFNGR1), interleukins (IL1B, IL1R, IL1R2, IL2, IL4, IL6, IL8, IL10, IL13, IL17A), nuclear factors of kappa light polypeptide gene enhancer in B cells (NFKB1 and NFKB2), and tumor necrosis factor alpha (TNFA).

RESULTS

After adjusting for relevant demographic and clinical characteristics, long daytime napping was associated with 12 SNPs from seven genes: 1) IFNG rs2069728; 2) IL1B rs1143642, rs1143627, and rs16944; 3) IL2 rs2069763; 4) IL6 rs4719714, rs1554606, and rs2069845; 5) IL17A rs3819024 and rs8193036; 6) NFKB1 rs4648110; and 7) NFKB2 rs1056890.

CONCLUSIONS

Cytokine genetic variations may have a role in physiological regulation of daytime napping as well as nocturnal sleep. Cytokine polymorphisms associated with long daytime napping could help identify adults with HIV who may benefit from targeted therapeutic interventions.

Inflammatory pathway genes associated with inter-individual variability in the trajectories of morning and evening fatigue in patients receiving chemotherapy

Fatigue, a highly prevalent and distressing symptom during chemotherapy (CTX), demonstrates diurnal and interindividual variability in severity. Little is known about the associations between variations in genes involved in inflammatory processes and morning and evening fatigue severity during CTX. The purposes of this study, in a sample of oncology patients (N=543) with breast, gastrointestinal (GI), gynecological (GYN), or lung cancer who received two cycles of CTX, were to determine whether variations in genes involved in inflammatory processes were associated with inter-individual variability in initial levels as well as in the trajectories of morning and evening fatigue. Patients completed the Lee Fatigue Scale to determine morning and evening fatigue severity a total of six times over two cycles of CTX. Using a whole exome array, 309 single nucleotide polymorphisms SNPs among the 64 candidate genes that passed all quality control filters were evaluated using hierarchical linear modeling (HLM). Based on the results of the HLM analyses, the final SNPs were evaluated for their potential impact on protein function using two bioinformational tools. The following inflammatory pathways were represented: chemokines (3 genes); cytokines (12 genes); inflammasome (11 genes); Janus kinase/signal transducers and activators of transcription (JAK/STAT, 10 genes); mitogen-activated protein kinase/jun amino-terminal kinases (MAPK/JNK, 3 genes); nuclear factor-kappa beta (NFkB, 18 genes); and NFkB and MAP/JNK (7 genes). After controlling for self-reported and genomic estimates of race and ethnicity, polymorphisms in six genes from the cytokine (2 genes); inflammasome (2 genes); and NFkB (2 genes) pathways were associated with both morning and evening fatigue. Polymorphisms in six genes from the inflammasome (1 gene); JAK/STAT (1 gene); and NFkB (4 genes) pathways were associated with only morning fatigue. Polymorphisms in three genes from the inflammasome (2 genes) and the NFkB (1 gene) pathways were associated with only evening fatigue. Taken together, these findings add to the growing body of evidence that suggests that morning and evening fatigue are distinct symptoms.

Associations Between Neurotransmitter Genes and Fatigue and Energy Levels in Women After Breast Cancer Surgery

CONTEXT

Fatigue is a common problem in oncology patients. Less is known about decrements in energy levels and the mechanisms that underlie both fatigue and energy.

OBJECTIVES

In patients with breast cancer, variations in neurotransmitter genes between lower and higher fatigue latent classes and between the higher and lower energy latent classes were evaluated.

METHODS

Patients completed assessments before and monthly for six months after surgery. Growth mixture modeling was used to identify distinct latent classes for fatigue severity and energy levels. Thirty candidate genes involved in various aspects of neurotransmission were evaluated.

RESULTS

Eleven single-nucleotide polymorphisms or haplotypes (i.e., ADRB2 rs1042718, BDNF rs6265, COMT rs9332377, CYP3A4 rs4646437, GALR1 rs949060, GCH1 rs3783642, NOS1 rs9658498, NOS1 rs2293052, NPY1R Haplotype A04, SLC6A2 rs17841327, and 5HTTLPR + rs25531 in SLC6A4) were associated with latent class membership for fatigue. Seven single-nucleotide polymorphisms or haplotypes (i.e., NOS1 rs471871, SLC6A1 rs2675163, SLC6A1 Haplotype D01, SLC6A2 rs36027, SLC6A3 rs37022, SLC6A4 rs2020942, and TAC1 rs2072100) were associated with latent class membership for energy. Three of 13 genes (i.e., NOS1, SLC6A2, and SLC6A4) were associated with latent class membership for both fatigue and energy.

CONCLUSIONS

Molecular findings support the hypothesis that fatigue and energy are distinct, yet related symptoms. Results suggest that a large number of neurotransmitters play a role in the development and maintenance of fatigue and energy levels in breast cancer patients.

Polymorphisms in Cytokine Genes Are Associated With Higher Levels of Fatigue and Lower Levels of Energy in Women After Breast Cancer Surgery

CONTEXT

Little is known about the phenotypic and molecular characteristics associated with changes over time in fatigue and lack of energy in patients with breast cancer.

OBJECTIVES

The aim of this study was to identify subgroups (i.e., latent classes) of women with distinct fatigue and energy trajectories; evaluate for differences in phenotypic characteristics between the latent classes for fatigue and energy; and evaluate for associations between polymorphisms in genes for pro- and anti-inflammatory cytokines, their receptors, and their transcriptional regulators and latent class membership.

METHODS

Patients were enrolled before and followed for six months after breast cancer surgery. Latent class analyses were done to identify subgroups of patients with distinct fatigue and energy trajectories. Candidate gene analyses were done to identify cytokine genes associated with these two symptoms.

RESULTS

For both fatigue and lack of energy, two distinct latent classes were identified. Phenotypic characteristics associated with the higher fatigue class were younger age, higher education, lower Karnofsky Performance Status score, higher comorbidity, higher number of lymph nodes removed, and receipt of chemotherapy (CTX). Polymorphisms in interleukin (IL) 1β and IL10 were associated with membership in the higher fatigue class. Phenotypic characteristics associated with the lower energy class included: a lower Karnofsky Performance Status score and a higher comorbidity score. A polymorphism in IL1R1 was associated with membership in the lower energy class.

CONCLUSION

Within each latent class, the severity of fatigue and decrements in energy were relatively stable over the first six months after breast cancer surgery. Distinct phenotypic characteristics and genetic polymorphisms were associated with membership in the higher fatigue and lower energy classes.

Role of Some Predominant Host Immunomodulators' Single Nucleotide Polymorphisms in Severity of Hepatitis B Virus and Hepatitis C Virus Infection

Hepatitis B and C infections can be either acute or chronic. The chronic infection can culminate in liver cirrhosis and hepatocellular carcinoma. Influence of the host genetic makeup on conversion of acute to chronic infection, development of cirrhosis, and hepatocellular carcinoma is an interesting area of research. Variability in different immune system genes may account for such differences in the outcome of infection. This article discusses single nucleotide polymorphisms in different host immunomodulator genes that have been frequently reported to influence the outcome of infection and severity of disease. The genetic variability could be utilized for the prediction of disease outcome and treatment responses.

Bayesian modeling for genetic association in case-control studies: accounting for unknown population substructure

A two-stage parametric Bayesian method is proposed to examine the association between a candidate gene and the occurrence of a disease after accounting for population substructure. This procedure, implemented via a Markov chain Monte Carlo numerical integration technique, first estimates the posterior probability of different unknown population substructures and then integrates this information into a disease-gene association model through the technique of Bayesian model averaging. The model relaxes certain assumptions of previous analyses and provides a unified computational framework to obtain an estimate of the log odds ratio parameter corresponding to the genetic factor after allowing for the allele frequencies to vary across subpopulations. The uncertainty in estimating the population substructure is taken into account while providing credible intervals for parameters in the disease-gene association model. Simulations on unmatched case-control studies that mimic an admixed Argentinean population are performed to demonstrate the statistical properties of our model. The method is also applied to a real data set coming from a genetic association study on obesity.

Genetic variation associated with preterm birth in African-American women

BACKGROUND

Preterm birth is considered a multifactorial condition; however, emerging evidence suggests that genetic variation among individuals may have an important role. Prior studies have suggested that single-nucleotide polymorphisms associated with genes related to the immune system, and particularly the maternal inflammatory response, may be associated with an increased risk of preterm delivery.

OBJECTIVE

The objective of the study was to identify single-nucleotide polymorphisms associated with spontaneous preterm birth <37 weeks within a cohort of African-American women.

STUDY DESIGN

This is a secondary analysis of a randomized trial that evaluated periodontal disease and preterm birth. Women were enrolled between 6 and 20 weeks' gestation at 3 prenatal care clinics between 2004 and 2007. Maternal DNA samples were collected and analyzed using a custom 1536 single-nucleotide polymorphismgenotyping array designed to assess genes involved in inflammation. Women were included in this study if they self-identified as African American. We excluded women with a multiple gestation or an indicated preterm delivery. We performed allele- and genotype-based analyses to evaluate the association between spontaneous preterm birth and tag single-nucleotide polymorphisms. We used a logistic regression to adjust for prior preterm birth in our genotype-based analysis. In a subgroup analysis, we compared women who delivered at <34 weeks' gestation to women who delivered at term. Within the microarray, we identified ancestry informative markers and compared global ancestry estimates among women who delivered preterm with those who delivered at term.

RESULTS

Of the 833 African-American women in the study with genotype data, 77 women (9.2%) had a spontaneous preterm birth, whereas 756 women delivered at term. In an allele-based analysis, 4 single-nucleotide polymorphisms related to the genes for protein kinase C-α (PRKCA) were associated with increased risk of spontaneous preterm birth <37 weeks, whereas a single single-nucleotide polymorphism related to fms-related tyrosine kinase 1 (FLT1) was associated with spontaneous preterm birth <34 weeks. A genotype-based analysis revealed similar associations between single-nucleotide polymorphisms related to the PRKCA genes and spontaneous premature delivery. Additionally, single-nucleotide polymorphisms related to matrix metalloproteinase-2 (MMP2), tissue inhibitor of matrix metalloproteinase-2 (TIMP2), and interleukin 16 (IL16) genes were associated with spontaneous preterm birth <37 weeks in genotype-based analysis. Genetic variants related to MMP2, matrix metalloproteinase-1 (MMP1), and leukemia inhibitory factor receptor antisense RNA 1 (LIFR-AS1) genes were associated with higher rates of preterm birth <34 weeks. Ancestry estimates were similar between the women who had a spontaneous preterm birth and those who delivered at term.

CONCLUSION

We identified tag single-nucleotide polymorphisms related to 7 genes that are critical to inflammation, extracellular remodeling, and cell signaling that were associated with spontaneous preterm birth in African-American women. Specifically, we found a strong association with the PRKCA gene. Genetic variation in these regions of the genome may be important in the pathogenesis of preterm birth. Our results should be considered in the design of future genomic studies in prematurity.

Detecting hybridization using ancient DNA

It is well established that related species hybridize and that this can have varied but significant effects on speciation and environmental adaptation. It should therefore come as no surprise that hybridization is not limited to species that are alive today. In the last several decades, advances in technologies for recovering and sequencing DNA from fossil remains have enabled the assembly of high-coverage genome sequences for a growing diversity of organisms, including many that are extinct. Thanks to the development of new statistical approaches for detecting and quantifying admixture from genomic data, genomes from extinct populations have proven useful both in revealing previously unknown hybridization events and informing the study of hybridization between living organisms. Here, we review some of the key recent statistical innovations for detecting ancient hybridization using genomewide sequence data and discuss how these innovations have revised our understanding of human evolutionary history.

Phenotypic and molecular characteristics associated with various domains of quality of life in oncology patients and their family caregivers

PURPOSE

Not all oncology patients and their family caregivers (FCs) experience the same quality of life (QOL). The purposes of this study were to identify latent classes of oncology patients (n = 168) and their FCs (n = 85) with distinct physical, psychological, social, and spiritual well-being trajectories from prior to through 4 months after the completion of radiation therapy and to evaluate for demographic, clinical, and genetic characteristics that distinguished between these latent classes.

METHODS

Using growth mixture modeling, two latent classes were found for three (i.e., physical, psychological, and social well-being) of the four QOL domains evaluated.

RESULTS

Across these three domains, the largest percentage of participants reported relatively high well-being scores across the 6 months of the study. Across these three QOL domains, patients and FCs who were younger, female, belonged to an ethnic minority group, had children at home, had multiple comorbid conditions, or had a lower functional status, were more likely to be classified in the lower QOL class. The social well-being domain was the only domain that had a polymorphism in nuclear factor kappa beta 2 (NFKB2) associated with latent class membership. Carrying one or two doses of the rare allele for rs7897947 was associated with a 54 % decrease in the odds of belonging to the lower social well-being class [OR (95 % CI) = .46 (.21, .99), p = .049].

CONCLUSIONS

These findings suggest that a number of phenotypic and molecular characteristics contribute to differences in QOL in oncology patients and their FCs.

A Continuous Correlated Beta Process Model for Genetic Ancestry in Admixed Populations

Admixture and recombination create populations and genomes with genetic ancestry from multiple source populations. Analyses of genetic ancestry in admixed populations are relevant for trait and disease mapping, studies of speciation, and conservation efforts. Consequently, many methods have been developed to infer genome-average ancestry and to deconvolute ancestry into continuous local ancestry blocks or tracts within individuals. Current methods for local ancestry inference perform well when admixture occurred recently or hybridization is ongoing, or when admixture occurred in the distant past such that local ancestry blocks have fixed in the admixed population. However, methods to infer local ancestry frequencies in isolated admixed populations still segregating for ancestry do not exist. In the current paper, I develop and test a continuous correlated beta process model to fill this analytical gap. The method explicitly models autocorrelations in ancestry frequencies at the population-level and uses discriminant analysis of SNP windows to take advantage of ancestry blocks within individuals. Analyses of simulated data sets show that the method is generally accurate such that ancestry frequency estimates exhibited low root-mean-square error and were highly correlated with the true values, particularly when large (±10 or ±20) SNP windows were used. Along these lines, the proposed method outperformed post hoc inference of ancestry frequencies from a traditional hidden Markov model (i.e., the linkage model in structure), particularly when admixture occurred more distantly in the past with little on-going gene flow or was followed by natural selection. The reliability and utility of the method was further assessed by analyzing genetic ancestry in an admixed human population (Uyghur) and three populations from a hybrid zone between Mus domesticus and M. musculus. Considerable variation in ancestry frequencies was detected within and among chromosomes in the Uyghur, with a large region of excess French ancestry harboring a gene with a known disease association. Similar variation was detected in the mouse hybrid zone, with notable constancy in regions of excess ancestry among admixed populations. By filling what has been an analytical gap, the proposed method should be a useful tool for many biologists. A computer program (popanc), written in C++, has been developed based on the proposed method and is available on-line at http://sourceforge.net/projects/popanc/.

Birth weight modifies the association between central nervous system gene variation and adult body mass index

Genome wide association studies have identified ~100 loci associated with body mass index (BMI). Persons with low birth weight have an increased risk of metabolic disorders. We postulate that normal mechanisms of body weight regulation are disrupted in subjects with low birth weight. The present analyses included 2215 African American women from the Black Women's Health Study, and were based on genotype data on 20 BMI-associated loci and self-reported data on birth weight, weight at age 18 and adult weight. We used general linear models to assess the association of individual single-nucleotide polymorphisms (SNPs) with BMI at age 18 and later in adulthood within strata of birth weight (above and below the median, 3200 g). Three SNPs (rs1320330 near TMEM18, rs261967 near PCSK1 and rs17817964 in FTO), and a genetic score combining these three variants, showed significant interactions with birth weight in relation to BMI. Among women with birth weight <3200 g, there was an inverse association between genetic score and BMI; beta-coefficient=-0.045 (95% confidence intervals (CI) -0.104, 0.013) for BMI at age 18, and -0.055 (95% CI -0.112, 0.002) for adult BMI. Among women with birth weight ⩾3200 g, genetic score was positively associated with BMI: beta-coefficient=0.110 (95% CI 0.051, 0.169) for BMI at age 18 (P for interaction=0.0002), and 0.112 (95% CI 0.054, 0.170) for adult BMI (P for interaction<0.0001). Because TMEM18, PCSK1 and FTO are highly expressed in the central nervous system (CNS), our results suggest that low-birth weight may disrupt mechanisms of CNS body weight regulation.