All-cause mortality and risk factors in a cohort of retired military male veterans, Xi'an, China: an 18-year follow up study

<p>Abstract</p> <p>Background</p> <p>Risk factors of all-cause mortality have not been reported in Chinese retired military veterans. The objective of the study was to examine the risk factors and proportional mortality in a Chinese retired military male cohort.</p> <p>Methods</p> <p>A total of 1268 retired military men aged 55 or older were examined physically and interviewed using a standard questionnaire in 1987. The cohort was followed up every two years and the study censored date was June30, 2005 with a follow-up of up to 18 years. Death certificates were obtained from hospitals and verified by two senior doctors. Data were entered (double entry) by Foxbase, and analysis was carried out by SAS for Windows 8.2. Multivariate Cox proportional hazard regression model was used to compute hazard ratio (HR) and 95% confidence interval (CI).</p> <p>Results</p> <p>The total person-years of follow-up was 18766.28. Of the initial cohort of 1268 men, 491 had died, 748 were alive and 29 were lost to follow up. Adjusted mortality (adjusted for age, blood pressure, body mass index, cholesterol, triglycerides, alcohol, exercise, and existing disease) was 2,616 per 100,000 person years. The proportional mortality of cancer, vascular disease and Chronic Obstructive Pulmonary Disease (COPD) were 39.71%, 28.10% and 16.90% respectively. Multivariate analysis showed that age, cigarettes per day, systolic blood pressure, triglyceride, family history of diseases (hypertension, stroke and cancer), existing diseases (stroke, diabetes and cancer), body mass index, and age of starting smoking were associated with all-cause mortality, HR (95%CI) was1.083(1.062–1.104), 1.026(1.013–1.039), 1.009(1.003–1.015), 1.002(1.001–1.003), 1.330(1.005–1.759), 1.330(1.005–1.759), 1.444(1.103–1.890), 2.237(1.244–4.022), 1.462(1.042–2.051), 2.079(1.051–4.115), 0.963(0.931–0.996)and 0.988(0.978–0.999)respectively. Compared with never-smokers, current smokers had increased risks of total mortality [HR 1.369(1.083–1.731)], CHD [HR 1.805 (1.022–3.188)], and lung cancer [HR 2.939 (1.311–6.585)].</p> <p>Conclusion</p> <p>The three leading causes of diseases were cancer, CHD and stroke, and COPD. Aging, cigarette smoking, high systolic blood pressure, high triglyceride, family history of cancer, hypertension and stroke, existing cases recovering from stroke, diabetes and cancer, underweight, younger age of smoking were risk factors for all-cause mortality. Quitting cigarette smoking, maintaining normal blood pressure, triglyceride and weight are effect control strategies to prevent premature mortality in this military cohort.</p

Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4

We conducted a combined genome-wide association study (GWAS) of 7,481 individuals with bipolar disorder (cases) and 9,250 controls as part of the Psychiatric GWAS Consortium. Our replication study tested 34 SNPs in 4,496 independent cases with bipolar disorder and 42,422 independent controls and found that 18 of 34 SNPs had P < 0.05, with 31 of 34 SNPs having signals with the same direction of effect (P = 3.8 x 10(-7)). An analysis of all 11,974 bipolar disorder cases and 51,792 controls confirmed genome-wide significant evidence of association for CACNA1C and identified a new intronic variant in ODZ4. We identified a pathway comprised of subunits of calcium channels enriched in bipolar disorder association intervals. Finally, a combined GWAS analysis of schizophrenia and bipolar disorder yielded strong association evidence for SNPs in CACNA1C and in the region of NEK4-ITIH1-ITIH3-ITIH4. Our replication results imply that increasing sample sizes in bipolar disorder will confirm many additional loci

Genetic pleiotropy between multiple sclerosis and schizophrenia but not bipolar disorder: differential involvement of immune-related gene loci

Converging evidence implicates immune abnormalities in schizophrenia (SCZ), and recent genome-wide association studies (GWAS) have identified immune-related single-nucleotide polymorphisms (SNPs) associated with SCZ. Using the conditional false discovery rate (FDR) approach, we evaluated pleiotropy in SNPs associated with SCZ (n=21\u2009856) and multiple sclerosis (MS) (n=43\u2009879), an inflammatory, demyelinating disease of the central nervous system. Because SCZ and bipolar disorder (BD) show substantial clinical and genetic overlap, we also investigated pleiotropy between BD (n=16\u2009731) and MS. We found significant genetic overlap between SCZ and MS and identified 21 independent loci associated with SCZ, conditioned on association with MS. This enrichment was driven by the major histocompatibility complex (MHC). Importantly, we detected the involvement of the same human leukocyte antigen (HLA) alleles in both SCZ and MS, but with an opposite directionality of effect of associated HLA alleles (that is, MS risk alleles were associated with decreased SCZ risk). In contrast, we found no genetic overlap between BD and MS. Considered together, our findings demonstrate genetic pleiotropy between SCZ and MS and suggest that the MHC signals may differentiate SCZ from BD susceptibility

All SNPs are not created equal: genome-wide association studies reveal a consistent pattern of enrichment among functionally annotated SNPs

Recent results indicate that genome-wide association studies (GWAS) have the potential to explain much of the heritability of common complex phenotypes, but methods are lacking to reliably identify the remaining associated single nucleotide polymorphisms (SNPs). We applied stratified False Discovery Rate (sFDR) methods to leverage genic enrichment in GWAS summary statistics data to uncover new loci likely to replicate in independent samples. Specifically, we use linkage disequilibrium-weighted annotations for each SNP in combination with nominal p-values to estimate the True Discovery Rate (TDR = 1−FDR) for strata determined by different genic categories. We show a consistent pattern of enrichment of polygenic effects in specific annotation categories across diverse phenotypes, with the greatest enrichment for SNPs tagging regulatory and coding genic elements, little enrichment in introns, and negative enrichment for intergenic SNPs. Stratified enrichment directly leads to increased TDR for a given p-value, mirrored by increased replication rates in independent samples. We show this in independent Crohn's disease GWAS, where we find a hundredfold variation in replication rate across genic categories. Applying a well-established sFDR methodology we demonstrate the utility of stratification for improving power of GWAS in complex phenotypes, with increased rejection rates from 20% in height to 300% in schizophrenia with traditional FDR and sFDR both fixed at 0.05. Our analyses demonstrate an inherent stratification among GWAS SNPs with important conceptual implications that can be leveraged by statistical methods to improve the discovery of loci

Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis

BACKGROUND: Findings from family and twin studies suggest that genetic contributions to psychiatric disorders do not in all cases map to present diagnostic categories. We aimed to identify specific variants underlying genetic effects shared between the five disorders in the Psychiatric Genomics Consortium: autism spectrum disorder, attention deficit-hyperactivity disorder, bipolar disorder, major depressive disorder, and schizophrenia. METHODS: We analysed genome-wide single-nucleotide polymorphism (SNP) data for the five disorders in 33,332 cases and 27,888 controls of European ancestory. To characterise allelic effects on each disorder, we applied a multinomial logistic regression procedure with model selection to identify the best-fitting model of relations between genotype and phenotype. We examined cross-disorder effects of genome-wide significant loci previously identified for bipolar disorder and schizophrenia, and used polygenic risk-score analysis to examine such effects from a broader set of common variants. We undertook pathway analyses to establish the biological associations underlying genetic overlap for the five disorders. We used enrichment analysis of expression quantitative trait loci (eQTL) data to assess whether SNPs with cross-disorder association were enriched for regulatory SNPs in post-mortem brain-tissue samples. FINDINGS: SNPs at four loci surpassed the cutoff for genome-wide significance (p<5×10(-8)) in the primary analysis: regions on chromosomes 3p21 and 10q24, and SNPs within two L-type voltage-gated calcium channel subunits, CACNA1C and CACNB2. Model selection analysis supported effects of these loci for several disorders. Loci previously associated with bipolar disorder or schizophrenia had variable diagnostic specificity. Polygenic risk scores showed cross-disorder associations, notably between adult-onset disorders. Pathway analysis supported a role for calcium channel signalling genes for all five disorders. Finally, SNPs with evidence of cross-disorder association were enriched for brain eQTL markers. INTERPRETATION: Our findings show that specific SNPs are associated with a range of psychiatric disorders of childhood onset or adult onset. In particular, variation in calcium-channel activity genes seems to have pleiotropic effects on psychopathology. These results provide evidence relevant to the goal of moving beyond descriptive syndromes in psychiatry, and towards a nosology informed by disease cause. FUNDING: National Institute of Mental Health