93 research outputs found

    Axonal swellings are related to type 2 diabetes, but not to distal diabetic sensorimotor polyneuropathy

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    Aims/hypothesis Distal diabetic sensorimotor polyneuropathy (DSP) is a common complication of diabetes with many patients showing a reduction of intraepidermal nerve fibre density (IENFD) from skin biopsy, a validated and sensitive diagnostic tool for the assessment of DSP. Axonal swelling ratio is a morphological quantification altered in DSP. It is, however, unclear if axonal swellings are related to diabetes or DSP. The aim of this study was to investigate how axonal swellings in cutaneous nerve fibres are related to type 2 diabetes mellitus, DSP and neuropathic pain in a well-defined cohort of patients diagnosed with type 2 diabetes. Methods A total of 249 participants, from the Pain in Neuropathy Study (UK) and the International Diabetic Neuropathy Consortium (Denmark), underwent a structured neurological examination, nerve conduction studies, quantitative sensory testing and skin biopsy. The study included four groups: healthy control study participants without diabetes (n = 45); participants with type 2 diabetes without DSP (DSP−; n = 31); and participants with evidence of DSP (DSP+; n = 173); the last were further separated into painless DSP+ (n = 74) and painful DSP+ (n = 99). Axonal swellings were defined as enlargements on epidermal-penetrating fibres exceeding 1.5 μm in diameter. Axonal swelling ratio is calculated by dividing the number of axonal swellings by the number of intraepidermal nerve fibres. Results Median (IQR) IENFD (fibres/mm) was: 6.7 (5.2–9.2) for healthy control participants; 6.2 (4.4–7.3) for DSP−; 1.3 (0.5–2.2) for painless DSP+; and 0.84 (0.4–1.6) for painful DSP+. Swelling ratios were calculated for all participants and those with IENFD > 1.0 fibre/mm. When only those participants with IENFD > 1.0 fibre/mm were included, the axonal swelling ratio was higher in participants with type 2 diabetes when compared with healthy control participants (p < 0.001); however, there was no difference between DSP− and painless DSP+ participants, or between painless DSP+ and painful DSP+ participants. The axonal swelling ratio correlated weakly with HbA1c (r = 0.16, p = 0.04), but did not correlate with the Toronto Clinical Scoring System (surrogate measure of DSP severity), BMI or type 2 diabetes duration. Conclusions/interpretation In individuals with type 2 diabetes where IENFD is >1.0 fibre/mm, axonal swelling ratio is related to type 2 diabetes but is not related to DSP or painful DSP. Axonal swellings may be an early marker of sensory nerve injury in type 2 diabetes

    Meta-analysis of genome-wide association studies identifies common susceptibility polymorphisms for colorectal and endometrial cancer near SH2B3 and TSHZ1

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    High-risk mutations in several genes predispose to both colorectal cancer (CRC) and endometrial cancer (EC). We therefore hypothesised that some lower-risk genetic variants might also predispose to both CRC and EC. Using CRC and EC genome-wide association series, totalling 13,265 cancer cases and 40,245 controls, we found that the protective allele [G] at one previously-identified CRC polymorphism, rs2736100 near TERT, was associated with EC risk (odds ratio (OR) = 1.08, P = 0.000167); this polymorphism influences the risk of several other cancers. A further CRC polymorphism near TERC also showed evidence of association with EC (OR = 0.92; P = 0.03). Overall, however, there was no good evidence that the set of CRC polymorphisms was associated with EC risk, and neither of two previously-reported EC polymorphisms was associated with CRC risk. A combined analysis revealed one genome-wide significant polymorphism, rs3184504, on chromosome 12q24 (OR = 1.10, P = 7.23 × 10−9) with shared effects on CRC and EC risk. This polymorphism, a missense variant in the gene SH2B3, is also associated with haematological and autoimmune disorders, suggesting that it influences cancer risk through the immune response. Another polymorphism, rs12970291 near gene TSHZ1, was associated with both CRC and EC (OR = 1.26, P = 4.82 × 10−8), with the alleles showing opposite effects on the risks of the two cancers

    Repositioning of the global epicentre of non-optimal cholesterol

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    High blood cholesterol is typically considered a feature of wealthy western countries1,2. However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world3 and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health4,5. However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low- and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol—which is a marker of cardiovascular risk—changed from those in western Europe such as Belgium, Finland, Greenland, Iceland, Norway, Sweden, Switzerland and Malta in 1980 to those in Asia and the Pacific, such as Tokelau, Malaysia, The Philippines and Thailand. In 2017, high non-HDL cholesterol was responsible for an estimated 3.9 million (95% credible interval 3.7 million–4.2 million) worldwide deaths, half of which occurred in east, southeast and south Asia. The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and personal interventions to improve nutrition and enhance access to treatment throughout the world.</p

    Repositioning of the global epicentre of non-optimal cholesterol

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    High blood cholesterol is typically considered a feature of wealthy western countries1,2. However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world3 and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health4,5. However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low- and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol�which is a marker of cardiovascular risk�changed from those in western Europe such as Belgium, Finland, Greenland, Iceland, Norway, Sweden, Switzerland and Malta in 1980 to those in Asia and the Pacific, such as Tokelau, Malaysia, The Philippines and Thailand. In 2017, high non-HDL cholesterol was responsible for an estimated 3.9 million (95 credible interval 3.7 million�4.2 million) worldwide deaths, half of which occurred in east, southeast and south Asia. The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and personal interventions to improve nutrition and enhance access to treatment throughout the world. © 2020, The Author(s), under exclusive licence to Springer Nature Limited

    Rising rural body-mass index is the main driver of the global obesity epidemic in adults

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    Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities 1,2 . This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity 3�6 . Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55 of the global rise in mean BMI from 1985 to 2017�and more than 80 in some low- and middle-income regions�was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing�and in some countries reversal�of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories. © 2019, The Author(s)
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