Transcript and protein signatures derived from shared molecular interactions across cancers are associated with mortality.

BACKGROUND: Characterization of shared cancer mechanisms have been proposed to improve therapy strategies and prognosis. Here, we aimed to identify shared cell-cell interactions (CCIs) within the tumor microenvironment across multiple solid cancers and assess their association with cancer mortality. METHODS: CCIs of each cancer were identified by NicheNet analysis of single-cell RNA sequencing data from breast, colon, liver, lung, and ovarian cancers. These CCIs were used to construct a shared multi-cellular tumor model (shared-MCTM) representing common CCIs across cancers. A gene signature was identified from the shared-MCTM and tested on the mRNA and protein level in two large independent cohorts: The Cancer Genome Atlas (TCGA, 9185 tumor samples and 727 controls across 22 cancers) and UK biobank (UKBB, 10,384 cancer patients and 5063 controls with proteomics data across 17 cancers). Cox proportional hazards models were used to evaluate the association of the signature with 10-year all-cause mortality, including sex-specific analysis. RESULTS: A shared-MCTM was derived from five individual cancers. A shared gene signature was extracted from this shared-MCTM and the most prominent regulatory cell type, matrix cancer-associated fibroblast (mCAF). The signature exhibited significant expression changes in multiple cancers compared to controls at both mRNA and protein levels in two independent cohorts. Importantly, it was significantly associated with mortality in cancer patients in both cohorts. The highest hazard ratios were observed for brain cancer in TCGA (HR [95%CI] = 6.90[4.64-10.25]) and ovarian cancer in UKBB (5.53[2.08-8.80]). Sex-specific analysis revealed distinct risks, with a higher mortality risk associated with the protein signature score in males (2.41[1.97-2.96]) compared to females (1.84[1.44-2.37]). CONCLUSION: We identified a gene signature from a comprehensive shared-MCTM representing common CCIs across different cancers and revealed the regulatory role of mCAF in the tumor microenvironment. The pathogenic relevance of the gene signature was supported by differential expression and association with mortality on both mRNA and protein levels in two independent cohorts.

Combining Mendelian randomization with the sibling comparison design.

Mendelian randomization (MR) is a popular epidemiologic study design that uses genetic variants as instrumental variables (IVs) to estimate causal effects, while accounting for unmeasured confounding. The validity of the MR design hinges on certain IV assumptions, which may sometimes be violated due to dynastic effects, population stratification, or assortative mating. Since these mechanisms act through parental factors it was recently suggested that the bias resulting from violations of the IV assumptions can be reduced by combing the MR design with the sibling comparison design, which implicitly controls for all factors that are constant within families. In this article, we provide a formal discussion of this combined MR-sibling design. We derive conditions under which the MR-sibling design is unbiased, and we relate these to the corresponding conditions for the standard MR and sibling comparison designs. We proceed by considering scenarios where all three designs are biased to some extent, and discuss under which conditions the MR-sibling design can be expected to have less bias than the other two designs. We finally illustrate the theoretical results and conclusions with an application to real data, in a study of low-density lipoprotein and diastolic blood pressure using data from the Swedish Twin Registry.

Hypogammaglobulinaemia during rituximab treatment in multiple sclerosis: A Swedish cohort study.

BACKGROUND AND PURPOSE: Mechanisms behind hypogammaglobulinaemia during rituximab treatment are poorly understood. METHODS: In this register-based multi-centre retrospective cohort study of multiple sclerosis (MS) patients in Sweden, 2745 patients from six participating Swedish MS centres were identified via the Swedish MS registry and included between 14 March 2008 and 25 January 2021. The exposure was treatment with at least one dose of rituximab for MS or clinically isolated syndrome, including data on treatment duration and doses. The degree of yearly decrease in immunoglobulin G (IgG) and immunoglobulin M (IgM) levels was evaluated. RESULTS: The mean decrease in IgG was 0.27 (95% confidence interval 0.17-0.36) g/L per year on rituximab treatment, slightly less in older patients, and without significant difference between sexes. IgG or IgM below the lower limit of normal (<6.7 or <0.27 g/L) was observed in 8.8% and 8.3% of patients, respectively, as nadir measurements. Six out of 2745 patients (0.2%) developed severe hypogammaglobulinaemia (IgG below 4.0 g/L) during the study period. Time on rituximab and accumulated dose were the main predictors for IgG decrease. Previous treatment with fingolimod and natalizumab, but not teriflunomide, dimethyl fumarate, interferons or glatiramer acetate, were significantly associated with lower baseline IgG levels by 0.80-1.03 g/L, compared with treatment-naïve patients. Switching from dimethyl fumarate or interferons was associated with an additional IgG decline of 0.14-0.19 g/L per year, compared to untreated. CONCLUSIONS: Accumulated dose and time on rituximab treatment are associated with a modest but significant decline in immunoglobulin levels. Previous MS therapies may influence additional IgG decline.

Advanced biological ageing predicts future risk for neurological diagnoses and clinical examination findings.

Age is a dominant risk factor for some of the most common neurological diseases. Biological ageing encompasses interindividual variation in the rate of ageing and can be calculated from clinical biomarkers or DNA methylation data amongst other approaches. Here, we tested the hypothesis that a biological age greater than one's chronological age affects the risk of future neurological diagnosis and the development of abnormal signs on clinical examination. We analysed data from the Swedish Adoption/Twin Study of Aging (SATSA): a cohort with 3175 assessments of 802 individuals followed-up over several decades. Six measures of biological ageing were generated: two physiological ages (created from bedside clinical measurements and standard blood tests) and four blood methylation age measures. Their effects on future stroke, dementia or Parkinson's disease diagnosis, or development of abnormal clinical signs, were determined using survival analysis, with and without stratification by twin pairs. Older physiological ages were associated with ischaemic stroke risk; for example one standard deviation advancement in baseline PhenoAgePhys or KDMAgePhys residual increased future ischaemic stroke risk by 29.2% [hazard ratio (HR): 1.29, 95% confidence interval (CI) 1.06-1.58, P = 0.012] and 42.9% (HR 1.43, CI 1.18-1.73, P = 3.1 × 10-4), respectively. In contrast, older methylation ages were more predictive of future dementia risk, which was increased by 29.7% (HR 1.30, CI 1.07-1.57, P = 0.007) per standard deviation advancement in HorvathAgeMeth. Older physiological ages were also positively associated with future development of abnormal patellar or pupillary reflexes, and the loss of normal gait. Measures of biological ageing can predict clinically relevant pathology of the nervous system independent of chronological age. This may help to explain variability in disease risk between individuals of the same age and strengthens the case for trials of geroprotective interventions for people with neurological disorders.

Repurposing antidiabetic drugs for rheumatoid arthritis: results from a two-sample Mendelian randomization study.

Despite increasing therapeutic options to treat rheumatoid arthritis (RA), many patients fail to reach treatment targets. The use of antidiabetic drugs like thiazolidinediones has been associated with lower RA risk. We aimed to explore the repurposing potential of antidiabetic drugs in RA prevention by assessing associations between genetic variation in antidiabetic drug target genes and RA using Mendelian randomization (MR). A two-sample MR design was used to estimate the association between the antidiabetic drug and RA risk using summary statistics from genome-wide association studies (GWAS). We selected independent genetic variants from the gene(s) that encode the target protein(s) of the investigated antidiabetic drug as instruments. We extracted the associations of instruments with blood glucose concentration and RA from the UK Biobank and a GWAS meta-analysis of clinically diagnosed RA, respectively. The effect of genetic variation in the drug target(s) on RA risk was estimated by the Wald ratio test or inverse-variance weighted method. Insulin and its analogues, thiazolidinediones, and sulfonylureas had valid genetic instruments (n = 1, 1, and 2, respectively). Genetic variation in thiazolidinedione target (gene: PPARG) was inversely associated with RA risk (odds ratio [OR] 0.38 per 0.1mmol/L glucose lowering, 95% confidence interval [CI] 0.20-0.73). Corresponding ORs (95%CIs) were 0.83 (0.44-1.55) for genetic variation in the targets of insulin and its analogues (gene: INSR), and 1.12 (0.83, 1.49) 1.25 (0.78-2.00) for genetic variation in the sulfonylurea targets (gene: ABCC8 and KCNJ11). In conclusion, genetic variation in the thiazolidinedione target is associated with a lower RA risk. The underlying mechanisms warrant further exploration.

Is Frailty Different in Younger Adults Compared to Old? Prevalence, Characteristics, and Risk Factors of Early-Life and Late-Life Frailty in Samples from Sweden and UK.

INTRODUCTION: Although frailty is commonly considered as a syndrome of old individuals, recent studies show that it can affect younger adults, too. Whether and how frailty differs in younger adults compared to old is however unknown. To this end, we analyzed the prevalence, characteristics, and risk factors of early-life (aged <65) and late-life (aged ≥65) frailty. METHODS: We analyzed individuals in the UK Biobank (N = 405,123) and Swedish Screening Across the Lifespan Twin (SALT; N = 43,641) study. Frailty index (FI) scores ≥0.21 were used to demarcate frailty. Characteristics of early-life versus late-life frailty were analyzed by collating the FI items (deficits) into domains and comparing the domain scores between younger and older frail individuals. Logistic regression was used to assess the risk factors of frailty. RESULTS: The pooled prevalence rates of frailty were 10.3% (95% confidence interval [CI]: 2.7-32.7), 14.4% (95% CI: 4.5-37.2), 19.2% (95% CI: 2.5-68.5) in individuals aged ≤55, 55-64, 65-74, respectively. Younger frail adults (aged <65) had higher scores in immunological, mental wellbeing, and pain-related domains, whereas older frail adults (aged ≥65) had higher scores in cardiometabolic, cancer, musculoskeletal, and sensory-related domains. Higher age, female sex, smoking, lower alcohol consumption, lower education, obesity, overweight, low income, and maternal smoking were similarly associated with the risk of early-life and late-life frailty. CONCLUSION: Frailty is prevalent also in younger age groups (aged <65) but differs in some of its characteristics from the old. The risk factors of frailty are nevertheless largely similar for early-life and late-life frailty.

Protein Nutritional Status and Frailty: A Mendelian Randomization Study.

BACKGROUND: Observational studies have suggested that better protein nutritional status may contribute to prevention of frailty. OBJECTIVE: We sought to examine this hypothesis using a Mendelian randomization (MR) analysis. METHODS: We conducted a two-sample MR study using GWAS summary statistics data of the UK Biobank. We applied genetically predicted serum albumin as a primary exposure measure and serum total protein as a secondary exposure measure. The outcome measure was the Rockwood frailty index (FI) based on 49 deficits from 356,432 individuals (53.3% of them were women, with a mean ± SD age of 56.7 ± 8.0 y. The association between serum protein measures and FI was mainly analyzed by use of the inverse variance weighted method. RESULTS: A genetically predicted serum albumin concentration was not statistically significantly associated with FI in the full sample. However, in women, we observed a preventive association between genetically predicted serum albumin and FI (ß = -0.172 per g/L; 95% CI: -0.336, -0.007; P = 0.041). In the full sample, genetically predicted serum total protein was inversely associated with FI (ß: -0.153 per g/L; 95% CI: -0.251, -0.056; P = 0.002). In both women and men, higher serum total protein was significantly inversely associated with FI; regression coefficients were -0.148 per g/L (95% CI: -0.287, -0.009; P = 0.037) for women, -0.154 per g/L (95% CI: -0.290, -0.018; P = 0.027) for men. CONCLUSIONS: The present MR study implies that better protein nutritional status modestly contributes to reducing the risk of frailty.

DNA methylation signatures of aggression and closely related constructs: A meta-analysis of epigenome-wide studies across the lifespan.

DNA methylation profiles of aggressive behavior may capture lifetime cumulative effects of genetic, stochastic, and environmental influences associated with aggression. Here, we report the first large meta-analysis of epigenome-wide association studies (EWAS) of aggressive behavior (N = 15,324 participants). In peripheral blood samples of 14,434 participants from 18 cohorts with mean ages ranging from 7 to 68 years, 13 methylation sites were significantly associated with aggression (alpha = 1.2 × 10-7; Bonferroni correction). In cord blood samples of 2425 children from five cohorts with aggression assessed at mean ages ranging from 4 to 7 years, 83% of these sites showed the same direction of association with childhood aggression (r = 0.74, p = 0.006) but no epigenome-wide significant sites were found. Top-sites (48 at a false discovery rate of 5% in the peripheral blood meta-analysis or in a combined meta-analysis of peripheral blood and cord blood) have been associated with chemical exposures, smoking, cognition, metabolic traits, and genetic variation (mQTLs). Three genes whose expression levels were associated with top-sites were previously linked to schizophrenia and general risk tolerance. At six CpGs, DNA methylation variation in blood mirrors variation in the brain. On average 44% (range = 3-82%) of the aggression-methylation association was explained by current and former smoking and BMI. These findings point at loci that are sensitive to chemical exposures with potential implications for neuronal functions. We hope these results to be a starting point for studies leading to applications as peripheral biomarkers and to reveal causal relationships with aggression and related traits.

Adiposity and the risk of dementia: mediating effects from inflammation and lipid levels.

While midlife adiposity is a risk factor for dementia, adiposity in late-life appears to be associated with lower risk. What drives the associations is poorly understood, especially the inverse association in late-life. Using results from genome-wide association studies, we identified inflammation and lipid metabolism as biological pathways involved in both adiposity and dementia. To test if these factors mediate the effect of midlife and/or late-life adiposity on dementia, we then used cohort data from the Swedish Twin Registry, with measures of adiposity and potential mediators taken in midlife (age 40-64, n = 5999) or late-life (age 65-90, n = 7257). Associations between body-mass index (BMI), waist-hip ratio (WHR), C-reactive protein (CRP), lipid levels, and dementia were tested in survival and mediation analyses. Age was used as the underlying time scale, and sex and education included as covariates in all models. Fasting status was included as a covariate in models of lipids. One standard deviation (SD) higher WHR in midlife was associated with 25% (95% CI 2-52%) higher dementia risk, with slight attenuation when adjusting for BMI. No evidence of mediation through CRP or lipid levels was present. After age 65, one SD higher BMI, but not WHR, was associated with 8% (95% CI 1-14%) lower dementia risk. The association was partly mediated by higher CRP, and suppressed when high-density lipoprotein levels were low. In conclusion, the negative effects of midlife adiposity on dementia risk were driven directly by factors associated with body fat distribution, with no evidence of mediation through inflammation or lipid levels. There was an inverse association between late-life adiposity and dementia risk, especially where the body's inflammatory response and lipid homeostasis is intact.

Deciphering the genetic and epidemiological landscape of mitochondrial DNA abundance.

Mitochondrial (MT) dysfunction is a hallmark of aging and has been associated with most aging-related diseases as well as immunological processes. However, little is known about aging, lifestyle and genetic factors influencing mitochondrial DNA (mtDNA) abundance. In this study, mtDNA abundance was estimated from the weighted intensities of probes mapping to the MT genome in 295,150 participants from the UK Biobank. We found that the abundance of mtDNA was significantly elevated in women compared to men, was negatively correlated with advanced age, higher smoking exposure, greater body-mass index, higher frailty index as well as elevated red and white blood cell count and lower mortality. In addition, several biochemistry markers in blood-related to cholesterol metabolism, ion homeostasis and kidney function were found to be significantly associated with mtDNA abundance. By performing a genome-wide association study, we identified 50 independent regions genome-wide significantly associated with mtDNA abundance which harbour multiple genes involved in the immune system, cancer as well as mitochondrial function. Using mixed effects models, we estimated the SNP-heritability of mtDNA abundance to be around 8%. To investigate the consequence of altered mtDNA abundance, we performed a phenome-wide association study and found that mtDNA abundance is involved in risk for leukaemia, hematologic diseases as well as hypertension. Thus, estimating mtDNA abundance from genotyping arrays has the potential to provide novel insights into age- and disease-relevant processes, particularly those related to immunity and established mitochondrial functions.

Frailty and the risk of dementia: is the association explained by shared environmental and genetic factors?

BACKGROUND: Frailty has been identified as a risk factor for cognitive impairment and dementia. However, it is not known whether familial factors, such as genetics and shared environmental factors, underlie this association. We analyzed the association between frailty and the risk of dementia in a large twin cohort and examined the role of familial factors in the association. METHODS: The Rockwood frailty index (FI) based on 44 health deficits was used to assess frailty. The population-level association between FI and the risk of all-cause dementia was analyzed in 41,550 participants of the Screening Across the Lifespan Twin (SALT) study (full sample, aged 41-97 years at baseline), using Cox and competing risk models. A subsample of 10,487 SALT participants aged 65 and older who received a cognitive assessment (cognitive sample) was used in a sensitivity analysis to assess the effect of baseline cognitive level on the FI-dementia association. To analyze the influence of familial effects on the FI-dementia association, a within-pair analysis was performed. The within-pair model was also used to assess whether the risk conferred by frailty varies by age at FI assessment. RESULTS: A total of 3183 individuals were diagnosed with dementia during the 19-year follow-up. A 10% increase in FI was associated with an increased risk of dementia (hazard ratio [HR] 1.17 (95% confidence interval [CI] 1.07, 1.18)) in the full sample adjusted for age, sex, education, and tobacco use. A significant association was likewise found in the cognitive sample, with an HR of 1.13 (95% CI 1.09, 1.20), adjusted for age, sex, and cognitive level at baseline. The associations were not attenuated when adjusted for APOE ɛ4 carrier status or considering the competing risk of death. After adjusting for familial effects, we found no evidence for statistically significant attenuation of the effect. The risk conferred by higher FI on dementia was constant after age 50 until very old age. CONCLUSIONS: A higher level of frailty predicts the risk of dementia and the association appears independent of familial factors. Targeting frailty might thus contribute to preventing or delaying dementia.

Frailty trajectories in three longitudinal studies of aging: Is the level or the rate of change more predictive of mortality?

BACKGROUND: frailty shows an upward trajectory with age, and higher levels increase the risk of mortality. However, it is less known whether the shape of frailty trajectories differs by age at death or whether the rate of change in frailty is associated with mortality. OBJECTIVES: to assess population frailty trajectories by age at death and to analyse whether the current level of the frailty index (FI) i.e. the most recent measurement or the person-specific rate of change is more predictive of mortality. METHODS: 3,689 individuals from three population-based cohorts with up to 15 repeated measurements of the Rockwood frailty index were analysed. The FI trajectories were assessed by stratifying the sample into four age-at-death groups: <70, 70-80, 80-90 and >90 years. Generalised survival models were used in the survival analysis. RESULTS: the FI trajectories by age at death showed that those who died at <70 years had a steadily increasing trajectory throughout the 40 years before death, whereas those who died at the oldest ages only accrued deficits from age ~75 onwards. Higher level of FI was independently associated with increased risk of mortality (hazard ratio 1.68, 95% confidence interval 1.47-1.91), whereas the rate of change was no longer significant after accounting for the current FI level. The effect of the FI level did not weaken with time elapsed since the last measurement. CONCLUSIONS: Frailty trajectories differ as a function of age-at-death category. The current level of FI is a stronger marker for risk stratification than the rate of change.

Replicating associations between DNA methylation and body mass index in a longitudinal sample of older twins.

BACKGROUND: There is an important interplay between epigenetic factors and body weight, and previous work has identified ten sites where DNA methylation is robustly associated with body mass index (BMI) cross-sectionally. However, interpretation of the associations is complicated by the substantial changes in BMI often occurring in late-life, and the fact that methylation is often driven by genetic variation. This study therefore investigated the longitudinal association between these ten sites and BMI from midlife to late-life, and whether associations persist after controlling for genetic factors. METHODS: We used data from 535 individuals (mean age 68) in the Swedish Adoption/Twin Study of Aging (SATSA) with longitudinal measures of both DNA methylation from blood samples and BMI, spanning up to 20 years. Methylation levels were measured with the Infinium Human Methylation 450K or Infinium MethylationEpic array, with seven of the ten sites passing quality control. Latent growth curve models were applied to investigate longitudinal associations between methylation and BMI, and between-within models to study associations within twin pairs, thus adjusting for genetic factors. RESULTS: Baseline DNA methylation levels at five of the seven sites were associated with BMI level at age 65 (cg00574958 [CPT1A]; cg11024682 [SREBF1]), and/or change (cg06192883 [MYO5C]; cg06946797 [RMI2]; cg08857797 [VPS25]). For four of the five sites, the associations remained comparable within twin pairs. However, the effects of cg06192883 were substantially attenuated within pairs. No change in DNA methylation was detected for any of the seven evaluated sites. CONCLUSION: Five of the seven sites investigated were associated with late-life level and/or change in BMI. The effects for four of the sites remained similar when examined within twin pairs, indicating that the associations are mainly environmentally driven. However, the substantial attenuation in the association between cg06192883 and late-life BMI within pairs points to the importance of genetic factors in this association.

Epigenome-wide analysis of frailty: Results from two European twin cohorts.

Epigenetics plays an important role in the aging process, but it is unclear whether epigenetic factors also influence frailty, an age-related state of physiological decline. In this study, we performed a meta-analysis of epigenome-wide association studies in four samples drawn from the Swedish Adoption/Twin Study of Aging (SATSA) and the Longitudinal Study of Aging Danish Twins (LSADT) to explore the association between DNA methylation and frailty. Frailty was defined using the frailty index (FI), and DNA methylation levels were measured in whole blood using Illumina's Infinium HumanMethylation450K and MethylationEPIC arrays. In the meta-analysis consisting of a total of 829 participants, we identified 589 CpG sites that were statistically significantly associated with either the continuous or categorical FI (false discovery rate <0.05). Many of these CpGs have previously been associated with age and age-related diseases. The identified sites were also largely directionally consistent in a longitudinal analysis using mixed-effects models in SATSA, where the participants were followed up to a maximum of 20 years. Moreover, we identified three differentially methylated regions within the MGRN1, MIR596, and TAPBP genes that have been linked to neuronal aging, tumor growth, and immune functions. Furthermore, our meta-analysis results replicated 34 of the 77 previously reported frailty-associated CpGs at p < 0.05. In conclusion, our findings demonstrate robust associations between frailty and DNA methylation levels in 589 novel CpGs, previously unidentified for frailty, and strengthen the role of neuronal/brain pathways in frailty.

Independent role of Alzheimer's disease genetics and C-reactive protein on cognitive ability in aging.

Apolipoprotein E (APOE) ε4, the strongest genetic risk factor for late onset Alzheimer's disease (LOAD), has been associated with cognitive decline independent from AD pathology, but the role for other LOAD risk genes in normal cognitive aging is less studied. We examined the effect of APOE ε4 and several different polygenic risk scores (PRS) for LOAD on cognitive level and decline in aging, using longitudinal data from the UK Biobank. While PRS-LOAD including all variants (except APOE) predicted cognitive level, APOE ε4 and PRS-LOAD based on 17 non-APOE gene variants with strong association to AD (p < 5e-8) predicted age-related decline in verbal numeric reasoning. The effect on decline were partly driven by 4 variants involved in the immune system. Those variants also predicted serum levels of the inflammatory marker C-reactive protein (CRP), but CRP did not mediate the effect on decline. Those findings suggest genetic variations in immune functions play a role in aspects of cognitive aging that may be independent of LOAD pathology as well as systemic inflammation measured by CRP.

Leukocyte DNA methylation in Alzheimer´s disease associated genes: replication of findings from neuronal cells.

Differences in gene-wide DNA methylation of the Alzheimer's disease (AD)-associated genes BIN1, HLA-DRB5, SORL1, SLC24A4, and ABCA7 are reported to be associated with AD in post-mortem brain samples. We investigated whether the same associations could be found in leukocytes collected pre-mortem. Using cohort data of 544 Swedish twins (204 dementia diagnoses), we replicated the findings in HLA-DRB5 and SLC24A4 at P < 0.05. However, co-twin control analyses indicated that the associations were partly explained by familial confounding. Thus, DNA methylation differences in HLA-DRB5 and SLC24A4 are present in both neuronal cells and leukocytes, and not fully explained familial factors.

Can frailty scores predict the incidence of cancer? Results from two large population-based studies.

While chronological age is the single biggest risk factor for cancer, it is less clear whether frailty, an age-related state of physiological decline, may also predict cancer incidence. We assessed the associations of frailty index (FI) and frailty phenotype (FP) scores with the incidence of any cancer and five common cancers (breast, prostate, lung, colorectal, melanoma) in 453,144 UK Biobank (UKB) and 36,888 Screening Across the Lifespan Twin study (SALT) participants, who aged 38-73 years and had no cancer diagnosis at baseline. During a median follow-up of 10.9 and 10.7 years, 53,049 (11.7%) and 4,362 (11.8%) incident cancers were documented in UKB and SALT, respectively. Using multivariable-adjusted Cox models, we found a higher risk of any cancer in frail vs. non-frail UKB participants, when defined by both FI (hazard ratio [HR] = 1.22; 95% confidence interval [CI] = 1.17-1.28) and FP (HR = 1.16; 95% CI = 1.11-1.21). The FI in SALT similarly predicted risk of any cancer (HR = 1.31; 95% CI = 1.15-1.49). Moreover, frailty was predictive of lung cancer in UKB, although this association was not observed in SALT. Adding frailty scores to models including age, sex, and traditional cancer risk factors resulted in little improvement in C-statistics for most cancers. In a within-twin-pair analysis in SALT, the association between FI and any cancer was attenuated within monozygotic but not dizygotic twins, indicating that it may partly be explained by genetic factors. Our findings suggest that frailty scores are associated with the incidence of any cancer and lung cancer, although their clinical utility for predicting cancers may be limited.

Genetic overlap between Parkinson's disease and inflammatory bowel disease.

Parkinson's disease and inflammatory bowel disease have been increasingly associated, implying shared pathophysiology. To explore biological explanations for the reported connection, we leveraged summary statistics of updated genome-wide association studies and characterized the genetic overlap between the two diseases. Aggregated genetic association data were available for 37 688 cases versus 981 372 controls for Parkinson's disease and 25 042 cases versus 34 915 controls for inflammatory bowel disease. Genetic correlation was estimated with the high-definition likelihood method. Genetic variants with joint association to both diseases were identified by conditional false discovery rate framework and further annotated to reveal shared loci, genes, and enriched pathways. For both Crohn's disease and ulcerative colitis, the two main subtypes of inflammatory bowel disease, we detected weak but statistically significant genetic correlations with Parkinson's disease (Crohn's disease: rg = 0.06, P = 0.01; ulcerative colitis: rg = 0.06, P = 0.03). A total of 1290 variants in 27 independent genomic loci were detected to associate with Parkinson's disease and Crohn's disease at conjunctional false discovery rate under 0.01 and 1359 variants in 15 loci were pleiotropic to Parkinson's disease and ulcerative colitis. Among the identified pleiotropic loci, 23 are novel and have never been associated with both phenotypes. A mixture of loci conferring either same or opposing genetic effects on two phenotypes was also observed. Positional and expression quantitative trait loci mapping prioritized 296 and 253 genes for Parkinson's disease with Crohn's disease and ulcerative colitis, respectively, among which only <10% are differentially expressed in both colon and substantia nigra. These genes were identified to overrepresent in pathways regulating gene expression and post-translational modification beyond several immune-related pathways enriched by major histocompatibility complex genes. In conclusion, we found robust evidence for a genetic link between Parkinson's disease and inflammatory bowel disease. The identified genetic overlap is complex at the locus and gene levels, indicating the presence of both synergistic and antagonistic pleiotropy. At the functional level, our findings implied a role of immune-centered mechanisms in the reported gut-brain connection.

Rare functional variants in the CRP and G6PC genes modify the relationship between obesity and serum C-reactive protein in white British population.

BACKGROUND: C-reactive protein (CRP) is a sensitive biomarker of inflammation with moderate heritability. The role of rare functional genetic variants in relation to serum CRP is understudied. We aimed to examine gene mutation burden of protein-altering (PA) and loss-of-function (LOF) variants in association with serum CRP, and to further explore the clinical relevance. METHODS: We included 161,430 unrelated participants of European ancestry from the UK Biobank. Of the rare (minor allele frequency <0.1%) and functional variants, 1,776,249 PA and 266,226 LOF variants were identified. Gene-based burden tests, linear regressions, and logistic regressions were performed to identify the candidate mutations at the gene and variant levels, to estimate the potential interaction effect between the identified PA mutation and obesity, and to evaluate the relative risk of 16 CRP-associated diseases. RESULTS: At the gene level, PA mutation burdens of the CRP (ß = -0.685, p = 2.87e-28) and G6PC genes (ß = 0.203, p = 1.50e-06) were associated with reduced and increased serum CRP concentration, respectively. At the variant level, seven PA alleles in the CRP gene decreased serum CRP, of which the per-allele effects were approximately three to seven times greater than that of a common variant in the same locus. The effects of obesity and central obesity on serum CRP concentration were smaller among the PA mutation carriers in the CRP (pinteraction = 0.008) and G6PC gene (pinteraction = 0.034) compared to the corresponding non-carriers. CONCLUSION: PA mutation burdens in the CRP and G6PC genes are strongly associated with decreased serum CRP concentrations. As serum CRP and obesity are important predictors of cardiovascular risks in clinics, our observations suggest taking rare genetic factors into consideration might improve the delivery of precision medicine.