Personalized Genetic Risk Counseling to Motivate Diabetes Prevention: A randomized trial

OBJECTIVE To examine whether diabetes genetic risk testing and counseling can improve diabetes prevention behaviors. RESEARCH DESIGN AND METHODS We conducted a randomized trial of diabetes genetic risk counseling among overweight patients at increased phenotypic risk for type 2 diabetes. Participants were randomly allocated to genetic testing versus no testing. Genetic risk was calculated by summing 36 single nucleotide polymorphisms associated with type 2 diabetes. Participants in the top and bottom score quartiles received individual genetic counseling before being enrolled with untested control participants in a 12-week, validated, diabetes prevention program. Middle-risk quartile participants were not studied further. We examined the effect of this genetic counseling intervention on patient self-reported attitudes, program attendance, and weight loss, separately comparing higher-risk and lower-risk result recipients with control participants. RESULTS The 108 participants enrolled in the diabetes prevention program included 42 participants at higher diabetes genetic risk, 32 at lower diabetes genetic risk, and 34 untested control subjects. Mean age was 57.9 ± 10.6 years, 61% were men, and average BMI was 34.8 kg/m2, with no differences among randomization groups. Participants attended 6.8 ± 4.3 group sessions and lost 8.5 ± 10.1 pounds, with 33 of 108 (30.6%) losing ≥5% body weight. There were few statistically significant differences in self-reported motivation, program attendance, or mean weight loss when higher-risk recipients and lower-risk recipients were compared with control subjects (P > 0.05 for all but one comparison). CONCLUSIONS Diabetes genetic risk counseling with currently available variants does not significantly alter self-reported motivation or prevention program adherence for overweight individuals at risk for diabetes

Race-Ethnic Differences in the Association of Genetic Loci with HbA1c levels and Mortality in U.S. Adults: The Third National Health and Nutrition Examination Survey (NHANES III)

Background: Hemoglobin A1c (HbA1c) levels diagnose diabetes, predict mortality and are associated with ten single nucleotide polymorphisms (SNPs) in white individuals. Genetic associations in other race groups are not known. We tested the hypotheses that there is race-ethnic variation in 1) HbA1c-associated risk allele frequencies (RAFs) for SNPs near SPTA1, HFE, ANK1, HK1, ATP11A, FN3K, TMPRSS6, G6PC2, GCK, MTNR1B; 2) association of SNPs with HbA1c and 3) association of SNPs with mortality. Methods We studied 3,041 non-diabetic individuals in the NHANES (National Health and Nutrition Examination Survey) III. We stratified the analysis by race/ethnicity (NHW: non-Hispanic white; NHB: non-Hispanic black; MA: Mexican American) to calculate RAF, calculated a genotype score by adding risk SNPs, and tested associations with SNPs and the genotype score using an additive genetic model, with type 1 error = 0.05. Results: RAFs varied widely and at six loci race-ethnic differences in RAF were significant (p < 0.0002), with NHB usually the most divergent. For instance, at ATP11A, the SNP RAF was 54% in NHB, 18% in MA and 14% in NHW (p < .0001). The mean genotype score differed by race-ethnicity (NHW: 10.4, NHB: 11.0, MA: 10.7, p < .0001), and was associated with increase in HbA1c in NHW (β = 0.012 HbA1c increase per risk allele, p = 0.04) and MA (β = 0.021, p = 0.005) but not NHB (β = 0.007, p = 0.39). The genotype score was not associated with mortality in any group (NHW: OR (per risk allele increase in mortality) = 1.07, p = 0.09; NHB: OR = 1.04, p = 0.39; MA: OR = 1.03, p = 0.71). Conclusion: At many HbA1c loci in NHANES III there is substantial RAF race-ethnic heterogeneity. The combined impact of common HbA1c-associated variants on HbA1c levels varied by race-ethnicity, but did not influence mortality

Polygenic type 2 diabetes prediction at the limit of common variant detection.

Genome-wide association studies (GWAS) may have reached their limit of detecting common type 2 diabetes (T2D)-associated genetic variation. We evaluated the performance of current polygenic T2D prediction. Using data from the Framingham Offspring (FOS) and the Coronary Artery Risk Development in Young Adults (CARDIA) studies, we tested three hypotheses: 1) a 62-locus genotype risk score (GRSt) improves T2D prediction compared with previous less inclusive GRSt; 2) separate GRS for \u3b2-cell (GRS\u3b2) and insulin resistance (GRSIR) independently predict T2D; and 3) the relationships between T2D and GRSt, GRS\u3b2, or GRSIR do not differ between blacks and whites. Among 1,650 young white adults in CARDIA, 820 young black adults in CARDIA, and 3,471 white middle-aged adults in FOS, cumulative T2D incidence was 5.9%, 14.4%, and 12.9%, respectively, over 25 years. The 62-locus GRSt was significantly associated with incident T2D in all three groups. In FOS but not CARDIA, the 62-locus GRSt improved the model C statistic (0.698 and 0.726 for models without and with GRSt, respectively; P < 0.001) but did not materially improve risk reclassification in either study. Results were similar among blacks compared with whites. The GRS\u3b2 but not GRSIR predicted incident T2D among FOS and CARDIA whites. At the end of the era of common variant discovery for T2D, polygenic scores can predict T2D in whites and blacks but do not outperform clinical models. Further optimization of polygenic prediction may require novel analytic methods, including less common as well as functional variants

The MedSeq Project: a randomized trial of integrating whole genome sequencing into clinical medicine

Background: Whole genome sequencing (WGS) is already being used in certain clinical and research settings, but its impact on patient well-being, health-care utilization, and clinical decision-making remains largely unstudied. It is also unknown how best to communicate sequencing results to physicians and patients to improve health. We describe the design of the MedSeq Project: the first randomized trials of WGS in clinical care. Methods/Design This pair of randomized controlled trials compares WGS to standard of care in two clinical contexts: (a) disease-specific genomic medicine in a cardiomyopathy clinic and (b) general genomic medicine in primary care. We are recruiting 8 to 12 cardiologists, 8 to 12 primary care physicians, and approximately 200 of their patients. Patient participants in both the cardiology and primary care trials are randomly assigned to receive a family history assessment with or without WGS. Our laboratory delivers a genome report to physician participants that balances the needs to enhance understandability of genomic information and to convey its complexity. We provide an educational curriculum for physician participants and offer them a hotline to genetics professionals for guidance in interpreting and managing their patients’ genome reports. Using varied data sources, including surveys, semi-structured interviews, and review of clinical data, we measure the attitudes, behaviors and outcomes of physician and patient participants at multiple time points before and after the disclosure of these results. Discussion The impact of emerging sequencing technologies on patient care is unclear. We have designed a process of interpreting WGS results and delivering them to physicians in a way that anticipates how we envision genomic medicine will evolve in the near future. That is, our WGS report provides clinically relevant information while communicating the complexity and uncertainty of WGS results to physicians and, through physicians, to their patients. This project will not only illuminate the impact of integrating genomic medicine into the clinical care of patients but also inform the design of future studies. Trial registration ClinicalTrials.gov identifier NCT0173656

Returning Individual Research Results from Digital Phenotyping in Psychiatry

Psychiatry is rapidly adopting digital phenotyping and artificial intelligence/machine learning tools to study mental illness based on tracking participants’ locations, online activity, phone and text message usage, heart rate, sleep, physical activity, and more. Existing ethical frameworks for return of individual research results (IRRs) are inadequate to guide researchers for when, if, and how to return this unprecedented number of potentially sensitive results about each participant’s real-world behavior. To address this gap, we convened an interdisciplinary expert working group, supported by a National Institute of Mental Health grant. Building on established guidelines and the emerging norm of returning results in participant-centered research, we present a novel framework specific to the ethical, legal, and social implications of returning IRRs in digital phenotyping research. Our framework offers researchers, clinicians, and Institutional Review Boards (IRBs) urgently needed guidance, and the principles developed here in the context of psychiatry will be readily adaptable to other therapeutic areas

Signal transduction in cells of the immune system in microgravity

Life on Earth developed in the presence and under the constant influence of gravity. Gravity has been present during the entire evolution, from the first organic molecule to mammals and humans. Modern research revealed clearly that gravity is important, probably indispensable for the function of living systems, from unicellular organisms to men. Thus, gravity research is no more or less a fundamental question about the conditions of life on Earth. Since the first space missions and supported thereafter by a multitude of space and ground-based experiments, it is well known that immune cell function is severely suppressed in microgravity, which renders the cells of the immune system an ideal model organism to investigate the influence of gravity on the cellular and molecular level. Here we review the current knowledge about the question, if and how cellular signal transduction depends on the existence of gravity, with special focus on cells of the immune system. Since immune cell function is fundamental to keep the organism under imnological surveillance during the defence against pathogens, to investigate the effects and possible molecular mechanisms of altered gravity is indispensable for long-term space flights to Earth Moon or Mars. Thus, understanding the impact of gravity on cellular functions on Earth will provide not only important informations about the development of life on Earth, but also for therapeutic and preventive strategies to cope successfully with medical problems during space exploration

Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose.

Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p<1x10-7 (adjusted for multiple hypothesis-testing with the IBC array). Two SNPs had significant joint effects in the overall model and significant main effects only in one smoking stratum: rs140637 (FBN1) in AA individuals had a significant main effect only among smokers, and rs1444261 (closest gene C2orf63) in EA individuals had a significant main effect only among nonsmokers. Three additional SNPs were identified as having potential interaction by exhibiting a significant main effects only in smokers: rs1801232 (CUBN) in AA individuals, rs12243326 (TCF7L2) in EA individuals, and rs4132670 (TCF7L2) in EA individuals. No SNP met significance for potential interaction with smoking on baseline FG. The identification of these loci provides evidence for genetic interactions with smoking exposure that may explain some of the heterogeneity in the association between smoking and T2D

Intermediate filament cytoskeleton of the liver in health and disease

Intermediate filaments (IFs) represent the largest cytoskeletal gene family comprising ~70 genes expressed in tissue specific manner. In addition to scaffolding function, they form complex signaling platforms and interact with various kinases, adaptor, and apoptotic proteins. IFs are established cytoprotectants and IF variants are associated with >30 human diseases. Furthermore, IF-containing inclusion bodies are characteristic features of several neurodegenerative, muscular, and other disorders. Acidic (type I) and basic keratins (type II) build obligatory type I and type II heteropolymers and are expressed in epithelial cells. Adult hepatocytes contain K8 and K18 as their only cytoplasmic IF pair, whereas cholangiocytes express K7 and K19 in addition. K8/K18-deficient animals exhibit a marked susceptibility to various toxic agents and Fas-induced apoptosis. In humans, K8/K18 variants predispose to development of end-stage liver disease and acute liver failure (ALF). K8/K18 variants also associate with development of liver fibrosis in patients with chronic hepatitis C. Mallory-Denk bodies (MDBs) are protein aggregates consisting of ubiquitinated K8/K18, chaperones and sequestosome1/p62 (p62) as their major constituents. MDBs are found in various liver diseases including alcoholic and non-alcoholic steatohepatitis and can be formed in mice by feeding hepatotoxic substances griseofulvin and 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC). MDBs also arise in cell culture after transfection with K8/K18, ubiquitin, and p62. Major factors that determine MDB formation in vivo are the type of stress (with oxidative stress as a major player), the extent of stress-induced protein misfolding and resulting chaperone, proteasome and autophagy overload, keratin 8 excess, transglutaminase activation with transamidation of keratin 8 and p62 upregulation