真的有健康的胖子吗？ | PLOS ONE 论文推荐

本文转载自微信公众号中国生物技术网（ID：biotech-china）

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众所周知，肥胖会导致糖尿病、高血压、心血管疾病和其他各种疾病的险。但是似乎肥胖人群中有15-20%的人并没有这种风险，也就是说这些人属于“健康的胖子”。这是为什么呢？且听科学家们的研究解释。

近日发表在 PLOS ONE 期刊上的这项研究（论文信息见文末），解释了一些胖子仍然保持健康的原因。

该研究确定了三种基因，它们似乎会影响脂肪是被区分开并且存储在身体外围还是会分解进入循环系统。如果血液中脂肪水平过高便会增加II型糖尿病的风险，还会导致心脏和肝脏的脂肪堆积。

哥本哈根大学的遗传学教授 Haja Kadarmideen 说：“能够存储大量脂肪的人可能会肥胖，但不见得不健康。”

过去的研究发现，虽然超重或者肥胖会导致糖尿病、肝脏疾病和心脏病风险增加，但是肥胖人士中的15-20%似乎并没有此类健康问题。

另一项有10万丹麦人参与的研究发现，身体质量指数（BMI）处于“超重”水平的人相比于BMI为“健康”, “体重不足”和“肥胖”的人寿命更长，这显得体重、健康和寿命之间的关系并不是那么的直截了当。

Kadarmideen说：“我们想要弄清楚一些肥胖的人仍然保持健康的原因。”

这项研究发现，个体的基因组成会影响健康问题突破了所谓的体重上限，而对于某些人来说，这个数值可能并不在“健康”BMI范围内。相反的，一些BMI在健康范围内的人（外表看起来很瘦却内脏肥厚）却会产生代谢问题，而这些代谢问题通常与肥胖相关。

这项研究有60名男性和女性参与，他们的肥胖呈现病态（BMI超过45），其中一半的人有代谢疾病，另一半的人则身体健康。参与者都接受了减肥手术。

科学家们扫描了数以万计的基因以发现两组之间的差异。最终，他们发现在这两组中有3种基因，其活性和潜在基因序列相关的特性非常不同。当科学家们进一步测试脂肪和组织样本中的基因活性时，他们得出结论，这些基因在调节脂肪在细胞中的运输和存储方面起到重要作用。该团队希望能够在更大规模的研究中复现这个发现。

在未来，可能能够基于个体的基因特性和其他生物标记制定个性化的健康BMI值。Kadarmideen 说：“这项发现为诊断、药物开发和以特定基因为靶向的治疗铺平了道路。”

他补充说，这项发现不应该被作为抛弃均衡饮食和锻炼的借口，因为这些生活方式对健康有着重要影响，而这与体重无关。

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相关论文信息

题目 Inter-Tissue Gene Co-Expression Networks between Metabolically Healthy and Unhealthy Obese Individuals

作者 Lisette J. A. Kogelman, Jingyuan Fu, Lude Franke, Jan Willem Greve, Marten Hofker, Sander S. Rensen, Haja N. Kadarmideen 

发表日期  December 1, 2016

DOI:http://dx.doi.org/10.1371/journal.pone.0167519

摘要 

Background

Obesity is associated with severe co-morbidities such as type 2 diabetes and nonalcoholic steatohepatitis. However, studies have shown that 10–25 percent of the severely obese individuals are metabolically healthy. To date, the identification of genetic factors underlying the metabolically healthy obese (MHO) state is limited. Systems genetics approaches have led to the identification of genes and pathways in complex diseases. Here, we have used such approaches across tissues to detect genes and pathways involved in obesity-induced disease development.

Methods

Expression data of 60 severely obese individuals was accessible, of which 28 individuals were MHO and 32 were metabolically unhealthy obese (MUO). A whole genome expression profile of four tissues was available: liver, muscle, subcutaneous adipose tissue and visceral adipose tissue. Using insulin-related genes, we used the weighted gene co-expression network analysis (WGCNA) method to build within- and inter-tissue gene networks. We identified genes that were differentially connected between MHO and MUO individuals, which were further investigated by homing in on the modules they were active in. To identify potentially causal genes, we integrated genomic and transcriptomic data using an eQTL mapping approach.

Results

Both IL-6 and IL1B were identified as highly differentially co-expressed genes across tissues between MHO and MUO individuals, showing their potential role in obesity-induced disease development. WGCNA showed that those genes were clustering together within tissues, and further analysis showed different co-expression patterns between MHO and MUO subnetworks. A potential causal role for metabolic differences under similar obesity state was detected for PTPRE, IL-6R and SLC6A5.

Conclusions

We used a novel integrative approach by integration of co-expression networks across tissues to elucidate genetic factors related to obesity-induced metabolic disease development. The identified genes and their interactions give more insight into the genetic architecture of obesity and the association with co-morbidities.

论文链接 http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0167519

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