Original articleLean non-alcoholic fatty liver disease and risk of incident diabetes in a euglycaemic population undergoing health check-ups: A cohort study
Introduction
Non-alcoholic fatty liver disease (NAFLD) is rapidly becoming a serious public-health issue, as it is associated with elevated rates of liver-related and -unrelated morbidity and mortality [1]. The overall prevalence of NAFLD is estimated to be 25% in the general population worldwide [2]. While NAFLD is typically linked to obesity, it can also develop in a substantial proportion of individuals with normal or even low body mass index (BMI) scores, a condition termed ‘lean NAFLD’ that is frequently overlooked in clinical practice [3], [4], [5].
Although the mechanisms involved in the development and progression of NAFLD in subjects with lean body status are not entirely understood, the current evidence suggests they may be different from those found in obesity [6], [7]. Moreover, limited prognostic studies have found that, in the long term, lean subjects with NAFLD are at higher risk of severe liver disease [8] and mortality [9] than those who are obese with NAFLD. These factors all deliver the key message that lean NAFLD is a distinct phenotype rather than simply a byproduct of BMI.
The liver is a key organ that plays critical roles in the regulation of systemic glucose and lipid metabolism [10]. A recent meta-analysis including 19 observational studies and a total of 296,439 participants convincingly demonstrated that NAFLD is significantly associated with a twofold higher risk of new-onset diabetes [random-effects hazard ratio (HR): 2.22, 95% confidence interval (CI): 1.84–2.60; I2 = 79.2%] [11]. However, data to elucidate the association between lean NAFLD and risk of type 2 diabetes mellitus (T2DM) are scarce. Moreover, the influence of gender on this association is another important factor that has yet to be studied.
Thus, the present longitudinal cohort study was conducted to investigate the effect of lean NAFLD on the risk of incident diabetes, with a particular focus on sexual dimorphism to fill in at least some of the research gaps in the field.
Section snippets
Data sources and study population
This observational cohort study used data from the North Carolina State University Libraries Dryad Data Repository (https://datadryad.org). Initially, the records of 20,944 subjects who participated in a comprehensive medical examination programme at Murakami Memorial Hospital between 2004 and 2015 were extracted by Okamura et al. [12], [13]. Details of the medical health checkup programme have been described previously elsewhere [13]. Subjects were excluded at baseline for the following
Results
The participants’ basic characteristics and lifestyle factors are summarized in Table 1. The study enrolled 14,482 subjects (mean age of 43.7 years, mean BMI of 22.1 kg/m2) and 54.5% were male (n = 7898). The proportions of lean without NAFLD, overweight/obese without NAFLD, lean with NAFLD and overweight/obese with NAFLD were 61.5% (n = 8900), 20.8% (n = 3008), 3.5% (n = 514) and 14.2% (n = 2060), respectively, in the entire study population.
Participants’ baseline characteristics according to
Discussion
In our present longitudinal study of 14,482 euglycaemic adults without IFG or diabetes at baseline, those with lean NAFLD diagnosed by ultrasound had a significantly higher risk of new-onset T2DM regardless of gender, albeit more pronounced in women. Notably, in our study participants, those with NAFLD who were lean had approximately the same risk of eventually developing diabetes as those with NAFLD who were overweight/obese, even though the former exhibited lower levels of metabolic syndrome
Funding
This study was supported by the National Natural Science Foundation of China (No. 81870507 and No. 81900675), and by a key research and development programme in Shaanxi Province (2019 KW-32).
Authors’ contributions
All authors contributed significantly. LMW and XC researched data, conducted the analysis, and drafted and revised the manuscript. HLJ and LC contributed to the study design and method, and analyzed and interpreted the data. YLL, ZTL and RXY helped with the statistical analyses and review of the database. All authors agree to be held accountable for all aspects of this work to ensure that questions related to the accuracy and integrity of any part of this work are appropriately investigated and
Competing interests
The authors have no conflicts of interest to declare.
Acknowledgments
We are grateful to Takuro Okamura and Michiaki Fukui and colleagues for sharing their scientific knowledge.
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Both these authors contributed equally to this work.