Effects of within-person variability in spot urinary sodium measurements on the associations with blood pressure and risk of cardiovascular disease in 0.5 Million adults in UK Biobank

Background

Randomised control trials have demonstrated direct positive and causal associations of 24-hr measurements of urinary sodium excretion on blood pressure. However, prospective studies, which often used spot (not 24-hr) measurements of urinary sodium, have reported J-shaped associations with higher risks of cardiovascular disease (CVD) at sodium intake <4 g/day. The reasons for the discrepant results are not fully understood, but have prompted some to question the World Health Organisation's recommendations to restrict sodium intake to <2.3g/day.

Purpose

We examined the effects of within-person variability in spot urinary sodium (UNa) measurements on immediate and delayed associations of UNa with blood pressure at baseline and at resurvey, and with incident cardiovascular disease in the UK Biobank (UKB).

Methods

Baseline spot urine samples were measured in 502,619 adults at baseline and in 20,346 participants who were resurveyed at 4 years after baseline. Linear regression was used to assess associations of baseline UNa measurements with systolic blood pressure (SBP; mmHg) at baseline and at resurvey. Cox regression was used estimate the associations between baseline measures of UNa with incident CVD events (recorded from linkage with hospital records). All analyses were adjusted for confounders and corrected for regression dilution bias.

Results

After excluding participants with prevalent diseases, the primary analyses involved 386,060 adults who were followed-up for a median of 7.8 years, during which ∼13,000 CVD events occurred. Estimated mean (SD) urinary sodium excretion was 77.4 mmol/L (SD 44.4, IQR = 42.8–103.7 mmol/L), and mean SBP/DBP were 137.5/82.3 (SD 18.5/10.1) mmHg, respectively. Within-person variability in UNa was high, with a self-correlation of 0.35 at 4 years between measurements. After adjustment for confounders and correction for regression dilution bias, a 100 mmol/L higher UNa was associated with an immediate 3.2 mmHg higher SBP (95% confidence interval [CI]: 2.8–3.6) in cross-sectional analyses (Figure 1). However, the corresponding associations of baseline UNa with SBP at resurvey was completely attenuated (p=0.20). The predicted risk of CVD was 1.06 (95% CI 1.06–1.07, p<0.001) for a 3.2 mmHg higher SBP, but the observed risk for a 100 mmol/L higher UNa was 0.95 (95% CI 0.82–1.10, p=0.47) (Figure 1).

Conclusions

While spot measurements of UNa were strongly associated with immediate effects on SBP, the magnitude of within-person variability in UNa precluded detection of associations with SBP several years after baseline or with risk of CVD. The extreme within-person variability in spot UNa may explain the discrepant results of the trials and observational studies of sodium and blood pressure.

Figure 1. Spot UNa with SBP and CVD in UK Biobank

Funding Acknowledgement

Type of funding source: Public grant(s) – National budget only. Main funding source(s): Core funding from the Medical Research Council-Population Health Research Unit, British Heart Foundation

Impact of a medical mobile phone app (QUiPP) for predicting preterm birth on the anxiety and decisional conflicts faced by women in threatened preterm labour

BACKGROUND

The QUiPP app is a free, validated mobile phone application (app) that supports clinical decision-making for women in threatened preterm labour by providing an individualised risk of delivery within clinically important time points. Alongside generating a percentage risk score, the QUiPP app also provides the risk score in an infographic donut chart, allowing the clinician to communicate with the woman in an easy to understand format. Informing women of their risk status using the QUIPP app may help to reduce anxiety in women and decrease decisional conflict.

METHOD

A subset of participants from the EQUIPTT study [REC Ref. 17/LO/1802] were asked to complete a questionnaire booklet which was used to evaluate decisional conflict and anxiety. Seven sites were randomised to the QUiPP app intervention (to use as a decision and communication tool) and six sites were randomised to the control (continued their normal practice). The first section of the questionnaire booklet was completed by the woman before her assessment, and the second section after. The pre and postassessment anxiety scores utilised the Visual Analogue Scale for Anxiety (Hornblow and Kidson, 1976). The Decisional Conflict Scale (O'Connor, 1995) measured decisional conflict post assessment. The data were then analysed to determine the impact of the QUiPP App on the anxiety and decisional conflicts faced by women in threatened preterm labour.

RESULTS

Questionnaires were completed by 221 women from 12 of the potential 13 sites. After exclusions 202 questionnaires were included in the analysis. There was a significant reduction in difference between anxiety scores before and after clinical assessment. While there were reductions in anxiety and decisional conflict for women who were aware of the QUiPP app use, this failed to reach statistical significance.

CONCLUSIONS

The QUiPP app has potential to reduce anxiety and decisional conflict in women who are aware that it is being used in their care. Additional work is required to ensure clinicians are aware of the QUiPP app and optimise using it as a communication tool when counselling women.

Migration and outbreaks of vaccine-preventable disease in Europe: a systematic analysis (1990-2019)

Background

Migrant populations (defined as foreign-born) in the EU/EEA may be one of several under-immunised populations yet their role in outbreaks of vaccine-preventable diseases (VPDs) has been poorly defined to date.

Methods

We did both a temporal analysis to map published reports of migrant-related outbreaks against data from the ECDC's Surveillance Atlas of Infectious Disease, and a systematic review (PROSPERO CRD42019157473; 1990-2019) adhering to PRISMA guidelines, to explore whether migrants are involved in outbreaks in Europe and which particular subpopulations may be at increased risk. Studies on VPD outbreaks (measles, mumps, rubella, diphtheria, pertussis, polio, hepatitis A, N meningitidis, and H influenzae) in migrants residing in the EU/EEA were included.

Results

46 studies were included, reporting on 50 VPD outbreaks across 13 EU/EEA countries, of which 98% (n = 49) occured since January 2000. Measles had the highest number of reports of outbreaks involving migrants (n = 21; 5043 cases), followed by varicella (n = 10; 595 cases) and hepatitis A (n = 10; 1226 cases). 21 (40%) of outbreaks were reported from shelters for asylum seekers and refugees (mainly varicella or measles). Of 27 outbreaks where the index case was defined, 20 (74.1%) were migrants, including 9 (33.3%) from Eastern Europe and 6 (22.2%) from Africa. When mapped against the ECDC timeline of measles outbreaks, migrant-related outbreaks coincide with Europe-wide peaks in measles incidence (in 2006, 2010, and 2018).

Conclusions

Migrants represent one key group involved in VPD outbreaks, with refugees/asylum seekers residing in shelters or camps particularly at risk. Measles accounted for 38% of all reported outbreaks. Improved data collection on migrant status across Europe is crucial to understanding the complex relationship between migration and occurrence of VPD outbreaks to inform policy decisions on the most effective strategies to prevent future outbreaks.

Key messages

Migrants represent one key group involved in vaccine-preventable diseases outbreaks in Europe. Refugees and asylum seekers may be particularly at risk.

Development and validation of predictive models for QUiPP App v.2: tool for predicting preterm birth in asymptomatic high-risk women

OBJECTIVES

Accurate mid-pregnancy prediction of spontaneous preterm birth (sPTB) is essential to ensure appropriate surveillance of high-risk women. Advancing the QUiPP App prototype, QUiPP App v.2 aimed to provide individualized risk of delivery based on cervical length (CL), quantitative fetal fibronectin (qfFN) or both tests combined, taking into account further risk factors, such as multiple pregnancy. Here we report development of the QUiPP App v.2 predictive models for use in asymptomatic high-risk women, and validation using a distinct dataset in order to confirm the accuracy and transportability of the QUiPP App, overall and within specific clinically relevant time frames.

METHODS

This was a prospective secondary analysis of data of asymptomatic women at high risk of sPTB recruited in 13 UK preterm birth clinics. Women were offered longitudinal qfFN testing every 2-4 weeks and/or transvaginal ultrasound CL measurement between 18 + 0 and 36 + 6 weeks' gestation. A total of 1803 women (3878 visits) were included in the training set and 904 women (1400 visits) in the validation set. Prediction models were created based on the training set for use in three groups: patients with risk factors for sPTB and CL measurement alone, with risk factors for sPTB and qfFN measurement alone, and those with risk factors for sPTB and both CL and qfFN measurements. Survival analysis was used to identify the significant predictors of sPTB, and parametric structures for survival models were compared and the best selected. The estimated overall probability of delivery before six clinically important time points (< 30, < 34 and < 37 weeks' gestation and within 1, 2 and 4 weeks after testing) was calculated for each woman and analyzed as a predictive test for the actual occurrence of each event. This allowed receiver-operating-characteristics curves to be plotted, and areas under the curve (AUC) to be calculated. Calibration was performed to measure the agreement between expected and observed outcomes.

RESULTS

All three algorithms demonstrated high accuracy for the prediction of sPTB at < 30, < 34 and < 37 weeks' gestation and within 1, 2 and 4 weeks of testing, with AUCs between 0.75 and 0.90 for the use of qfFN and CL combined, between 0.68 and 0.90 for qfFN alone, and between 0.71 and 0.87 for CL alone. The differences between the three algorithms were not statistically significant. Calibration confirmed no significant differences between expected and observed rates of sPTB within 4 weeks and a slight overestimation of risk with the use of CL measurement between 22 + 0 and 25 + 6 weeks' gestation.

CONCLUSIONS

The QUiPP App v.2 is a highly accurate prediction tool for sPTB that is based on a unique combination of biomarkers, symptoms and statistical algorithms. It can be used reliably in the context of communicating to patients the risk of sPTB. Whilst further work is required to determine its role in identifying women requiring prophylactic interventions, it is a reliable and convenient screening tool for planning follow-up or hospitalization for high-risk women. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

Development and validation of predictive models for QUiPP App v.2: tool for predicting preterm birth in women with symptoms of threatened preterm labor

OBJECTIVE

To develop enhanced prediction models to update the QUiPP App prototype, a tool providing individualized risk of spontaneous preterm birth (sPTB), for use in women with symptoms of threatened preterm labor (TPTL), incorporating risk factors, transvaginal ultrasound assessment of cervical length (CL) and cervicovaginal fluid quantitative fetal fibronectin (qfFN) test results.

METHODS

Participants were pregnant women between 23 + 0 and 34 + 6 weeks' gestation with symptoms of TPTL, recruited as part of four prospective cohort studies carried out at 16 UK hospitals between October 2010 and October 2017. The training set comprised all women whose outcomes were known in May 2017 (n = 1032). The validation set comprised women whose outcomes were gathered between June 2017 and March 2018 (n = 506). Parametric survival models were developed for three combinations of predictors: risk factors plus qfFN test results alone, risk factors plus CL alone, and risk factors plus both qfFN and CL. The best models were selected using the Akaike and Bayesian information criteria. The estimated probability of sPTB < 30, < 34 or < 37 weeks' gestation and within 1 or 2 weeks of testing was calculated and receiver-operating-characteristics (ROC) curves were created to demonstrate the diagnostic ability of the prediction models.

RESULTS

Predictive statistics were similar between the training and the validation sets at most outcome time points and for each combination of predictors. Areas under the ROC curves (AUC) demonstrated that all three algorithms had good accuracy for the prediction of sPTB at < 30, < 34 and < 37 weeks' gestation and within 1 and 2 weeks' post-testing in the validation set, particularly the model combining risk factors plus qfFN alone (AUC: 0.96 at < 30 weeks; 0.85 at < 34 weeks; 0.77 at < 37 weeks; 0.91 at < 1 week from testing; and 0.92 at < 2 weeks from testing).

CONCLUSIONS

Validation of the new prediction models suggests that the QUiPP App v.2 can reliably calculate risk of sPTB in women with TPTL. Use of the QUiPP App in practice could lead to better targeting of intervention, while providing reassurance and avoiding unnecessary intervention in women at low risk. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

Racial differences in myocardial deformation in obese children: Significance of inflammatory state

BACKGROUND AND AIMS

The association between racial differences in myocardial deformation and cardiometabolic risk factors is unknown in obese children. Our objective was to: 1) investigate for racial differences in myocardial deformation between white and black obese children and 2) identify biomarkers associated with these observed racial differences. We hypothesized that decreased myocardial deformation observed in black obese children could be accounted for by the differences in the markers of metabolic syndrome between the groups.

METHODS AND RESULTS

Obese children were recruited prospectively. All clinical and laboratory tests for the metabolic syndrome were conducted during a single assessment using a standardized protocol. Speckle-tracking echocardiography was performed to obtain longitudinal and circumferential measures of deformation. 310 patients were included in the analysis; 158 (51%) white and 152 (49%) black. The median age was 11.3 years (IQR 5.9). Blacks demonstrated worse longitudinal strain (-14.7 ± 2.7% vs. -15.4 ± 2.9%, p = 0.04). There was no difference in circumferential strain between the groups. Multivariable linear regression showed a significant relationship between longitudinal strain and hsCRP (β = 0.16, p = 0.03) and HOMA-IR (β = 0.15, p = 0.04); there was no independent association between longitudinal strain and race.

CONCLUSION

Black subjects demonstrated worse longitudinal strain than whites. Only hsCRP and HOMA-IR levels, not race, had an independent association with longitudinal strain, suggesting that the observed racial differences in longitudinal strain may be secondary to differences in inflammation and insulin resistance between the groups.

Marie M, Stickney K, VanBuecken D, Vellek B, Webber C, Allen L, Bollyk J, Hilderman N, Ismail H, Lamola S, Sanda S, Vendettuoli H, Tridgell D, Monzavi R, Bock M, Fisher L, Halvorson M, Jeandron D, Kim M, Wood J, Geffner M, Kaufman F, Parkman R, Salazar C, Goland R, Clynes R, Cook S, Freeby M, Pat Gallagher M, Gandica R, Greenberg E, Kurland A, Pollak S, Wolk A, Chan M, Koplimae L, Levine E, Smith K, Trast J, DiMeglio L, Blum J, Evans-Molina C, Hufferd R, Jagielo B, Kruse C, Patrick V, Rigby M, Spall M, Swinney K, Terrell J, Christner L, Ford L, Lynch S, Menendez M, Merrill P, Pescovitz M, Rodriguez H, Alleyn C, Baidal D, Fay S, Gaglia J, Resnick B, Szubowicz S, Weir G, Benjamin R, Conboy D, deManbey A, Jackson R, Jalahej H, Orban T, Ricker A, Wolfsdorf J, Zhang HH, Wilson D, Aye T, Baker B, Barahona K, Buckingham B, Esrey K, Esrey T, Fathman G, Snyder R, Aneja B, Chatav M, Espinoza O, Frank E, Liu J, Perry J, Pyle R, Rigby A, Riley K, Soto A, Gitelman S, Adi S, Anderson M, Berhel A, Breen K, Fraser K, Gerard-Gonzalez A, Jossan P, Lustig R, Moassesfar S, Mugg A, Ng D, Prahalod P, Rangel-Lugo M, Sanda S, Tarkoff J, Torok C, Wesch R, Aslan I, Buchanan J, Cordier J, Hamilton C, Hawkins L, Ho T, Jain A, Ko K, Lee T, Phelps S, Rosenthal S, Sahakitrungruang T, Stehl L, Taylor L, Wertz M, Wong J, Philipson L, Briars R, Devine N, Littlejohn E, Grant T, Gottlieb P, Klingensmith G, Steck A, Alkanani A, Bautista K, Bedoy R, Blau A, Burke B, Cory L, Dang M, Fitzgerald-Miller L, Fouts A, Gage V, Garg S, Gesauldo P, Gutin R, Hayes C, Hoffman M, Ketchum K, Logsden-Sackett N, Maahs D, Messer L, Meyers L, Michels A, Peacock S, Rewers M, Rodriguez P, Sepulbeda F, Sippl R, Steck A, Taki I, Tran BK, Tran T, Wadwa RP, Zeitler P, Barker J, Barry S, Birks L, Bomsburger L, Bookert T, Briggs L, Burdick P, Cabrera R, Chase P, Cobry E, Conley A, Cook G, Daniels J, DiDomenico D, Eckert J, Ehler A, Eisenbarth G, Fain P, Fiallo-Scharer R, Frank N, Goettle H, Haarhues M, Harris S, Horton L, Hutton J, Jeffrrey J, Jenison R, Jones K, Kastelic W, King MA, Lehr D, Lungaro J, Mason K, Maurer H, Nguyen L, Proto A, Realsen J, Schmitt K, Schwartz M, Skovgaard S, Smith J, Vanderwel B, Voelmle M, Wagner R, Wallace A, Walravens P, Weiner L, Westerhoff B, Westfall E, Widmer K, Wright H, Schatz D, Abraham A, Atkinson M, Cintron M, Clare-Salzler M, Ferguson J, Haller M, Hosford J, Mancini D, Rohrs H, Silverstein J, Thomas J, Winter W, Cole G, Cook R, Coy R, Hicks E, Lewis N, Marks J, Pugliese A, Blaschke C, Matheson D, Pugliese A, Sanders-Branca N, Ray Arce LA, Cisneros M, Sabbag S, Moran A, Gibson C, Fife B, Hering B, Kwong C, Leschyshyn J, Nathan B, Pappenfus B, Street A, Boes MA, Peterson Eck S, Finney L, Albright Fischer T, Martin A, Jacqueline Muzamhindo C, Rhodes M, Smith J, Wagner J, Wood B, Becker D, Delallo K, Diaz A, Elnyczky B, Libman I, Pasek B, Riley K, Trucco M, Copemen B, Gwynn D, Toledo F, Rodriguez H, Bollepalli S, Diamond F, Eyth E, Henson D, Lenz A, Shulman D, Raskin P, Adhikari S, Dickson B, Dunnigan E, Lingvay I, Pruneda L, Ramos-Roman M, Raskin P, Rhee C, Richard J, Siegelman M, Sturges D, Sumpter K, White P, Alford M, Arthur J, Aviles-Santa ML, Cordova E, Davis R, Fernandez S, Fordan S, Hardin T, Jacobs A, Kaloyanova P, Lukacova-Zib I, Mirfakhraee S, Mohan A, Noto H, Smith O, Torres N, Wherrett D, Balmer D, Eisel L, Kovalakovska R, Mehan M, Sultan F, Ahenkorah B, Cevallos J, Razack N, Jo Ricci M, Rhode A, Srikandarajah M, Steger R, Russell WE, Black M, Brendle F, Brown A, Moore D, Pittel E, Robertson A, Shannon A, Thomas JW, Herold K, Feldman L, Sherwin R, Tamborlane W, Weinzimer S, Toppari J, Kallio T, Kärkkäinen M, Mäntymäki E, Niininen T, Nurmi B, Rajala P, Romo M, Suomenrinne S, Näntö-Salonen K, Simell O, Simell T, Bosi E, Battaglia M, Bianconi E, Bonfanti R, Grogan P, Laurenzi A, Martinenghi S, Meschi F, Pastore M, Falqui L, Teresa Muscato M, Viscardi M, Bingley P, Castleden H, Farthing N, Loud S, Matthews C, McGhee J, Morgan A, Pollitt J, Elliot-Jones R, Wheaton C, Knip M, Siljander H, Suomalainen H, Colman P, Healy F, Mesfin S, Redl L, Wentworth J, Willis J, Farley M, Harrison L, Perry C, Williams F, Mayo A, Paxton J, Thompson V, Volin L, Fenton C, Carr L, Lemon E, Swank M, Luidens M, Salgam M, Sharma V, Schade D, King C, Carano R, Heiden J, Means N, Holman L, Thomas I, Madrigal D, Muth T, Martin C, Plunkett C, Ramm C, Auchus R, Lane W, Avots E, Buford M, Hale C, Hoyle J, Lane B, Muir A, Shuler S, Raviele N, Ivie E, Jenkins M, Lindsley K, Hansen I, Fadoju D, Felner E, Bode B, Hosey R, Sax J, Jefferies C, Mannering S, Prentis R, She J, Stachura M, Hopkins D, Williams J, Steed L, Asatapova E, Nunez S, Knight S, Dixon P, Ching J, Donner T, Longnecker S, Abel K, Arcara K, Blackman S, Clark L, Cooke D, Plotnick L, Levin P, Bromberger L, Klein K, Sadurska K, Allen C, Michaud D, Snodgrass H, Burghen G, Chatha S, Clark C, Silverberg J, Wittmer C, Gardner J, LeBoeuf C, Bell P, McGlore O, Tennet H, Alba N, Carroll M, Baert L, Beaton H, Cordell E, Haynes A, Reed C, Lichter K, McCarthy P, McCarthy S, Monchamp T, Roach J, Manies S, Gunville F, Marosok L, Nelson T, Ackerman K, Rudolph J, Stewart M, McCormick K, May S, Falls T, Barrett T, Dale K, Makusha L, McTernana C, Penny-Thomas K, Sullivan K, Narendran P, Robbie J, Smith D, Christensen R, Koehler B, Royal C, Arthur T, Houser H, Renaldi J, Watsen S, Wu P, Lyons L, House B, Yu J, Holt H, Nation M, Vickers C, Watling R, Heptulla R, Trast J, Agarwal C, Newell D, Katikaneni R, Gardner C, Del A, Rio A, Logan H, Collier C, Rishton G, Whalley A, Ali S, Ramtoola T, Quattrin L, Mastrandea A, House M, Ecker C, Huang C, Gougeon J, Ho D, Pacuad D, Dunger J, May C, O’Brien C, Acerini B, Salgin A, Thankamony R, Williams J, Buse G, Fuller M, Duclos J, Tricome H, Brown D, Pittard D, Bowlby A, Blue T, Headley S, Bendre K, Lewis K, Sutphin C, Soloranzo J, Puskaric H, Madison M, Rincon M, Carlucci R, Shridharani B, Rusk E, Tessman D, Huffman H, Abrams B, Biederman M, Jones V, Leathers W, Brickman P, Petrie D, Zimmerman J, Howard L, Miller R, Alemzadeh D, Mihailescu R, Melgozza-Walker N, Abdulla C, Boucher-Berry D, Ize-Ludlow R, Levy C, Swenson, Brousell N, Crimmins D, Edler T, Weis C, Schultz D, Rogers D, Latham C, Mawhorter C, Switzer W, Spencer P, Konstantnopoulus S, Broder J, Klein L, Knight L, Szadek G, Welnick B, Thompson R, Hoffman A, Revell J, Cherko K, Carter E, Gilson J, Haines G, Arthur B, Bowen W, Zipf P, Graves R, Lozano D, Seiple K, Spicer A, Chang J, Fregosi J, Harbinson C, Paulson S, Stalters P, Wright D, Zlock A, Freeth J, Victory H, Maheshwari A, Maheshwari T, Holmstrom J, Bueno R, Arguello J, Ahern L, Noreika V, Watson S, Hourse P, Breyer C, Kissel Y, Nicholson M, Pfeifer S, Almazan J, Bajaj M, Quinn K, Funk J, McCance E, Moreno R, Veintimilla A, Wells J, Cook S, Trunnel J, Henske S, Desai K, Frizelis F, Khan R, Sjoberg K, Allen P, Manning G, Hendry B, Taylor S, Jones W, Strader M, Bencomo T, Bailey L, Bedolla C, Roldan C, Moudiotis B, Vaidya C, Anning S, Bunce S, Estcourt E, Folland E, Gordon C, Harrill J, Ireland J, Piper L, Scaife K, Sutton S, Wilkins M, Costelloe J, Palmer L, Casas C, Miller M, Burgard C, Erickson J, Hallanger-Johnson P, Clark W, Taylor A, Lafferty S, Gillett C, Nolan M, Pathak L, Sondrol T, Hjelle S, Hafner J, Kotrba R, Hendrickson A, Cemeroglu T, Symington M, Daniel Y, Appiagyei-Dankah D, Postellon M, Racine L, Kleis K, Barnes S, Godwin H, McCullough K, Shaheen G, Buck L, Noel M, Warren S, Weber S, Parker I, Gillespie B, Nelson C, Frost J, Amrhein E, Moreland A, Hayes J, Peggram J, Aisenberg M, Riordan J, Zasa E, Cummings K, Scott T, Pinto A, Mokashi K, McAssey E, Helden P, Hammond L, Dinning S, Rahman S, Ray C, Dimicri S, Guppy H, Nielsen C, Vogel C, Ariza L, Morales Y, Chang R, Gabbay L, Ambrocio L, Manley R, Nemery W, Charlton P, Smith L, Kerr B, Steindel-Kopp M, Alamaguer D, Liljenquist G, Browning T, Coughenour M, Sulk E, Tsalikan M, Tansey J, Cabbage N. Identical and Nonidentical Twins: Risk and Factors Involved in Development of Islet Autoimmunity and Type 1 Diabetes

OBJECTIVE

There are variable reports of risk of concordance for progression to islet autoantibodies and type 1 diabetes in identical twins after one twin is diagnosed. We examined development of positive autoantibodies and type 1 diabetes and the effects of genetic factors and common environment on autoantibody positivity in identical twins, nonidentical twins, and full siblings.

RESEARCH DESIGN AND METHODS

Subjects from the TrialNet Pathway to Prevention Study (N = 48,026) were screened from 2004 to 2015 for islet autoantibodies (GAD antibody [GADA], insulinoma-associated antigen 2 [IA-2A], and autoantibodies against insulin [IAA]). Of these subjects, 17,226 (157 identical twins, 283 nonidentical twins, and 16,786 full siblings) were followed for autoantibody positivity or type 1 diabetes for a median of 2.1 years.

RESULTS

At screening, identical twins were more likely to have positive GADA, IA-2A, and IAA than nonidentical twins or full siblings (all P < 0.0001). Younger age, male sex, and genetic factors were significant factors for expression of IA-2A, IAA, one or more positive autoantibodies, and two or more positive autoantibodies (all P ≤ 0.03). Initially autoantibody-positive identical twins had a 69% risk of diabetes by 3 years compared with 1.5% for initially autoantibody-negative identical twins. In nonidentical twins, type 1 diabetes risk by 3 years was 72% for initially multiple autoantibody-positive, 13% for single autoantibody-positive, and 0% for initially autoantibody-negative nonidentical twins. Full siblings had a 3-year type 1 diabetes risk of 47% for multiple autoantibody-positive, 12% for single autoantibody-positive, and 0.5% for initially autoantibody-negative subjects.

CONCLUSIONS

Risk of type 1 diabetes at 3 years is high for initially multiple and single autoantibody-positive identical twins and multiple autoantibody-positive nonidentical twins. Genetic predisposition, age, and male sex are significant risk factors for development of positive autoantibodies in twins.

Long Paddock: climate risk and grazing information for Australian rangelands and grazing communities

The Queensland Government’s Long Paddock website has been redeveloped on Amazon Web Services cloud computing platform, to provide Australian rangelands and grazing communities (i.e. rural landholders, managers, pastoralists (graziers), researchers, advisors, students, consultants and extension providers) with easier access to seasonal climate and pasture condition information. The website provides free, tailored information and services to support management decisions to maximise productivity, while maintaining the natural resource base. For example, historical rainfall and pasture analyses (i.e. maps, posters and data) have been developed to assist in communicating the risk of multi-year droughts that are a feature of Queensland’s highly variable climate.