The transcriptional landscape of age in human peripheral blood

Disease incidences increase with age, but the molecular characteristics of ageing that lead to increased disease susceptibility remain inadequately understood. Here we perform a whole-blood gene expression meta-analysis in 14,983 individuals of European ancestry (including replication) and identify 1,497 genes that are differentially expressed with chronological age. The age-associated genes do not harbor more age-associated CpG-methylation sites than other genes, but are instead enriched for the presence of potentially functional CpG-methylation sites in enhancer and insulator regions that associate with both chronological age and gene expression levels. We further used the gene expression profiles to calculate the 'transcriptomic age' of an individual, and show that differences between transcriptomic age and chronological age are associated with biological features linked to ageing, such as blood pressure, cholesterol levels, fasting glucose, and body mass index. The transcriptomic prediction model adds biological relevance and complements existing epigenetic prediction models, and can be used by others to calculate transcriptomic age in external cohorts.Peer reviewe

A saturated map of common genetic variants associated with human height.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries

Atrial fibrillation genetic risk differentiates cardioembolic stroke from other stroke subtypes

AbstractObjectiveWe sought to assess whether genetic risk factors for atrial fibrillation can explain cardioembolic stroke risk.MethodsWe evaluated genetic correlations between a prior genetic study of AF and AF in the presence of cardioembolic stroke using genome-wide genotypes from the Stroke Genetics Network (N = 3,190 AF cases, 3,000 cardioembolic stroke cases, and 28,026 referents). We tested whether a previously-validated AF polygenic risk score (PRS) associated with cardioembolic and other stroke subtypes after accounting for AF clinical risk factors.ResultsWe observed strong correlation between previously reported genetic risk for AF, AF in the presence of stroke, and cardioembolic stroke (Pearson’s r=0.77 and 0.76, respectively, across SNPs with p &lt; 4.4 × 10−4 in the prior AF meta-analysis). An AF PRS, adjusted for clinical AF risk factors, was associated with cardioembolic stroke (odds ratio (OR) per standard deviation (sd) = 1.40, p = 1.45×10−48), explaining ∼20% of the heritable component of cardioembolic stroke risk. The AF PRS was also associated with stroke of undetermined cause (OR per sd = 1.07, p = 0.004), but no other primary stroke subtypes (all p &gt; 0.1).ConclusionsGenetic risk for AF is associated with cardioembolic stroke, independent of clinical risk factors. Studies are warranted to determine whether AF genetic risk can serve as a biomarker for strokes caused by AF.</jats:sec

Association of cardiac autonomic dysfunction with higher levels of plasma lipid metabolites in recent-onset type 2 diabetes

Abstract Aims/hypothesis Emerging evidence suggests that in addition to hyperglycaemia, dyslipidaemia could represent a contributing pathogenetic factor to diabetic neuropathy, while obesity and insulin resistance play a role in the development of diabetic cardiac autonomic neuropathy (CAN) characterised by reduced heart rate variability (HRV), particularly in type 2 diabetes. We hypothesised that distinct lipid metabolites are associated with diminished HRV in recent-onset type 2 diabetes rather than type 1 diabetes. Methods We analysed 127 plasma lipid metabolites (11 acylcarnitines, 39 NEFA, 12 sphingomyelins (SMs), 56 phosphatidylcholines and nine lysophosphatidylcholines) using MS in participants from the German Diabetes Study baseline cohort recently diagnosed with type 1 (n = 100) and type 2 diabetes (n = 206). Four time-domain HRV indices (number of normal-to-normal (NN) intervals &gt;50 ms divided by the number of all NN intervals [pNN50]; root mean square of successive differences [RMSSD]; SD of NN intervals [SDNN]; and SD of differences between adjacent NN intervals) and three frequency-domain HRV indices (very-low-frequency [VLF], low-frequency [LF] and high-frequency [HF] power spectrum) were computed from NN intervals recorded during a 3 h hyperinsulinaemic–euglycaemic clamp at baseline and in subsets of participants with type 1 (n = 60) and type 2 diabetes (n = 95) after 5 years. Results In participants with type 2 diabetes, after Bonferroni correction and rigorous adjustment, SDNN was inversely associated with higher levels of diacyl-phosphatidylcholine (PCaa) C32:0, PCaa C34:1, acyl-alkyl-phosphatidylcholine (PCae) C36:0, SM C16:0 and SM C16:1. SD of differences between NN intervals was inversely associated with PCaa C32:0, PCaa C34:1, PCaa C34:2, PCae C36:0 and SM C16:1, and RMSSD with PCae C36:0. For VLF power, inverse associations were found with PCaa C30:0, PCaa C32:0, PCaa C32:1, PCaa C34:2 and SM C16:1, and for LF power inverse associations were found with PCaa C32:0 and SM C16:1 (r = −0.242 to r = −0.349; p ≤ 0.0005 for all correlations). In contrast, no associations of lipid metabolites with measures of cardiac autonomic function were noted in participants recently diagnosed with type 1 diabetes. After 5 years, HRV declined due to ageing rather than diabetes, whereby prediction analyses for lipid metabolites were hampered. Conclusions/interpretation Higher plasma levels of specific lipid metabolites are closely linked to cardiac autonomic dysfunction in recent-onset type 2 diabetes but not type 1 diabetes, suggesting a role for perturbed lipid metabolism in the early development of CAN in type 2 diabetes. </jats:sec

Pronounced Reduction of Cutaneous Langerhans Cell Density in Recently Diagnosed Type 2 Diabetes

Immune-mediated processes have been implicated in the pathogenesis of diabetic polyneuropathy. Langerhans cells (LCs) are the sole dendritic cell type located in the healthy epidermis and exert tolerogenic immune functions. We aimed to determine whether alterations in cutaneous LC density and intraepidermal nerve fiber density (IENFD) are present in patients with recently diagnosed type 2 diabetes. Skin biopsy specimens from the distal leg from 96 type 2 diabetic patients and 75 healthy control subjects were used for quantification of LC density and IENFD. LCs and IENFs were labeled using immunohistochemistry. Nerve conduction studies, quantitative sensory testing, and neurological examination were used to assess peripheral nerve function. LC density was markedly reduced in the diabetic group compared with the control group, but did not correlate with reduced IENFD or peripheral nerve function. Multivariate linear regression analysis revealed a strong association between LC density and whole-body insulin sensitivity in women but not in men with diabetes. Prospective studies should establish whether the pronounced reduction of cutaneous LCs detected in recently diagnosed type 2 diabetes could promote a cutaneous immunogenic imbalance toward inflammation predisposing to polyneuropathy and foot ulcers.</jats:p

Differences in the prevalence of erectile dysfunction between novel subgroups of recent-onset diabetes

Abstract Aims/hypothesis In men with diabetes, the prevalence of erectile dysfunction increases with advanced age and longer diabetes duration and is substantially higher in men with type 2 diabetes than those with type 1 diabetes. This study aimed to evaluate the prevalence of erectile dysfunction among the five novel subgroups of recent-onset diabetes and determine the strength of associations between diabetes subgroups and erectile dysfunction. Methods A total of 351 men with recent-onset diabetes (&lt;1 year) from the German Diabetes Study baseline cohort and 124 men without diabetes were included in this cross-sectional study. Erectile dysfunction was assessed with the International Index of Erectile Function (IIEF) questionnaire. Poisson regression models were used to estimate associations between diabetes subgroups (each subgroup tested against the four other subgroups as reference) and erectile dysfunction (dependent binary variable), adjusting for variables used to define diabetes subgroups, high-sensitivity C-reactive protein and depression. Results The prevalence of erectile dysfunction was markedly higher in men with diabetes than in men without diabetes (23% vs 11%, p = 0.004). Among men with diabetes, the prevalence of erectile dysfunction was highest in men with severe insulin-resistant diabetes (SIRD) (52%), lowest in men with severe autoimmune diabetes (SAID) (7%), and intermediate in men with severe insulin-deficient diabetes (SIDD), mild obesity-related diabetes (MOD) and mild age-related diabetes (MARD) (31%, 18% and 29%, respectively). Men with SIRD had an adjusted RR of 1.93 (95% CI 1.04, 3.58) for prevalent erectile dysfunction (p = 0.038). Similarly, men with SIDD had an adjusted RR of 3.27 (95% CI 1.18, 9.10) (p = 0.023). In contrast, men with SAID and those with MARD had unadjusted RRs of 0.26 (95% CI 0.11, 0.58) (p = 0.001) and 1.52 (95% CI 1.04, 2.22) (p = 0.027), respectively. However, these associations did not remain statistically significant after adjustment. Conclusions/interpretation The high RRs for erectile dysfunction in men with recent-onset SIRD and SIDD point to both insulin resistance and insulin deficiency as major contributing factors to this complication, suggesting different mechanisms underlying erectile dysfunction in these subgroups. Graphical abstract </jats:sec