分析231种饮食摄入与性早熟之间的因果关系——一项双样本孟德尔随机化研究
Analyzing the Causal Relationship between 231 Dietary Intake and Precocious Puberty —A Two-Sample Mendelian Randomization Study
DOI: 10.12677/acm.2024.14112911, PDF, HTML, XML,   
作者: 陈 薇:承德医学院研究生院,河北 承德;邢台市人民医院儿童神经、内分泌科,河北 邢台;张艳玲, 李 静:邢台市人民医院儿童神经、内分泌科,河北 邢台;王秀锋:邢台市人民医院小儿康复科,河北 邢台
关键词: 饮食摄入性早熟孟德尔随机化Dietary Intake Precocious Puberty Mendelian Randomization
摘要: 目的:本文旨在将混杂因素的影响控制在最小的前提下,探讨特定的饮食摄入与性早熟(PP)发病的关系。方法:使用来自芬兰数据库(FinnGen)和英国生物样本库(UKB)的大规模全基因组关联研究(GWAS)汇总统计数据来探讨性早熟与231种饮食摄入之间的潜在关联。然后进行两样本孟德尔随机化(TSMR)分析,以进一步评估性早熟与饮食摄入之间的因果关系。结果:5种饮食摄入表现出正相关,即盐渍花生的摄入(ukb-b-1099) (OR = 1480.226, 95% CI = (14.460~151528.425), p = 0.002)、其他咸口小吃的摄入(ukb-b-18718) (OR = 326.312, 95% CI = (2.452~43431.149), p = 0.020)、西梅的摄入(ukb-b-3022) (OR = 1174.199, 95% CI = (6.603~208798.930), p = 0.007)、标准茶摄入量(ukb-b-3291) (OR = 1.011, 95% CI = (1.000~1.022), p = 0.040)及酒精摄入的频率(ukb-b-5799) (OR = 3.332, 95% CI = (1.491~7.448), p = 0.003);其余4种表现出负相关,即白鱼的摄入(ukb-b-5427) (OR = 0.004, 95% CI = (0.000~0.259), p = 0.010)、牛奶布丁的摄入(ukb-b-9857) (OR = 0.002, 95% CI = (0.000~0.297), p = 0.015)、煎饼的摄入(ukb-b-6500) (OR = 0.014, 95% CI = (0.000~0.808), p = 0.039)、平均每周摄入烈酒(ukb-b-1707) (OR = 0.039, 95% CI = (0.002~0.624), p = 0.022);此外,我们还发现性早熟与标准茶摄入量(ukb-b-3291) (OR = 0.402, 95% CI = (0.169~0.957), p = 0.04)、白鱼的摄入(ukb-b-5427) (OR = 0.998, 95% CI = (0.995~1.000), p = 0.038)存在反向因果关系。敏感性分析结果显示孟德尔随机化分析结果可靠。结论:盐渍花生、其他的咸口小吃、西梅、茶的摄入及酒精的摄入频率对性早熟存在致病效应;白鱼、牛奶布丁、煎饼的摄入及平均每周摄入烈酒与性早熟的延缓有关;患有性早熟可能会引起茶和白鱼的摄入量增加或减少。我们的研究结果为理解性早熟的发病机制提供了新的线索,重点关注会引起性早熟的饮食摄入,从而提供详细的饮食指导及干预,以期降低性早熟的发病率及年轻化趋势。
Abstract: Objective: This study aims to investigate the relationship between specific dietary intakes and the onset of precocious puberty (PP) while minimizing the influence of confounding factors. Methods: Summary statistics from large-scale Genome-Wide Association Studies (GWAS) from the Finnish database (FinnGen) and the UK Biobank (UKB) were utilized to explore potential associations between precocious puberty and 231 types of dietary intakes. Two-sampled Mendelian Randomization (TSMR) analysis was subsequently conducted to further assess the causal relationship between precocious puberty and dietary intakes. Results: Five dietary intakes showed positive correlations: intake of salted peanuts (ukb-b-1099) (OR = 1480.226, 95% CI = (14.460~151528.425), p = 0.002), intake of other salty snacks (ukb-b-18718) (OR = 326.312, 95% CI = (2.452~43431.149), p = 0.020), intake of prunes (ukb-b-3022) (OR = 1174.199, 95% CI = (6.603~208798.930), p = 0.007), standard tea intake (ukb-b-3291) (OR = 1.011, 95% CI = (1.000~1.022), p = 0.040), and frequency of alcohol intake (ukb-b-5799) (OR = 3.332, 95% CI = (1.491~7.448), p = 0.003). The remaining four showed negative correlations: intake of white fish (ukb-b-5427) (OR = 0.004, 95% CI = (0.000~0.259), p = 0.010), intake of milk pudding (ukb-b-9857) (OR = 0.002, 95% CI = (0.000~0.297), p = 0.015), intake of pancakes (ukb-b-6500) (OR = 0.014, 95% CI = (0.000~0.808), p = 0.039), and average weekly intake of spirits (ukb-b-1707) (OR = 0.039, 95% CI = (0.002~0.624), p = 0.022). Additionally, we found that precocious puberty has a reverse causal relationship with standard tea intake (ukb-b-3291) (OR = 0.402, 95% CI = (0.169~0.957), p = 0.04) and intake of white fish (ukb-b-5427) (OR = 0.998, 95% CI = (0.995~1.000), p = 0.038). Sensitivity analysis results indicated that the Mendelian Randomization analysis results were reliable. Conclusion: The intake of salted peanuts, other salty snacks, prunes, tea, and the frequency of alcohol intake have pathogenic effects on precocious puberty. The intake of white fish, milk pudding, pancakes, and the average weekly intake of spirits are associated with a delay in precocious puberty. Having precocious puberty may lead to increased or decreased intake of tea and white fish. Our findings provide new insights into understanding the pathogenesis of precocious puberty, focusing on dietary intakes that may induce precocious puberty, thereby offering detailed dietary guidance and interventions to reduce the incidence and youthful trend of precocious puberty.
文章引用:陈薇, 张艳玲, 李静, 王秀锋. 分析231种饮食摄入与性早熟之间的因果关系——一项双样本孟德尔随机化研究[J]. 临床医学进展, 2024, 14(11): 531-541. https://doi.org/10.12677/acm.2024.14112911

1. 引言

青春期是一个生物学上的成熟过程,此期儿童出现加速生长、骨骼快速成熟和第二性征的发育,这是一个复杂的过程,涉及遗传、代谢、环境、民族、地理和经济等因素[1]。人类的生殖成熟需要激活下丘脑–垂体–性腺(HPG)轴,下丘脑分泌促性腺激素释放激素(GnRH),刺激垂体分泌促性腺激素:促性腺激素(LH)和卵泡刺激素(FSH),它们作用于性腺(卵巢和睾丸),进而刺激其成熟、配子发生和类固醇激素的产生[2]。PP的定义是女孩在8岁之前、男孩在9岁之前出现第二性征的发育。研究发现,青春期时间的改变对人类的身心均会造成有害影响,与成人身材矮小、肥胖、高血压、2型糖尿病、心血管疾病、雌激素依赖性癌症(尤其是乳腺癌)不良心理结局、风险增加有关,且可能会因为出现抑郁、自杀念头和行为问题,进而影响寿命[3] [4]。PP的发病率在女孩与男孩中约为15:1,不同国家和不同性别之间的发病率存在差异,美国女孩的患病率为0.05%~0.1% [3];丹麦女孩的患病率为0.2%,男孩的患病率 < 0.05% [5];韩国男孩的患病率 < 0.05%,女孩的患病率 < 0.01%,且女孩的患病率呈现出上升趋势[6];西班牙男孩的患病率约为0.05%,女孩的患病率约为0.04% [7]。尽管发病率存在一定的差异,但近年来在许多地区都发现了许多年龄更小的PP患者[8],甚至有学者建议将女孩PP的诊断年龄降低到7岁[9]-[11],这反映了PP的发病率在逐渐上升且呈现出年轻化的趋势。

饮食营养状况被认为是影响青春期发育的重要因素之一,25%的青春期时间变化的问题可以通过儿童时期的饮食营养解释,除此之外还与基因、心理、社会环境等因素有关[12]。先前的动物实验和观察性研究中已经发现了饮食对PP存在影响,但由于研究人群、饮食评估方法的不同及混杂因素的影响,迄今为止关于饮食摄入与青春期开始之间关联的证据存在较大的差异。因此,有必要选择更加严谨的方法探讨饮食摄入与青春期开始时间的关系。

综上,本文将从遗传变异视角引入,以数据库中最新的饮食摄入和PP的数据为支撑,借助TSMR方法进行研究,从而推断特殊的饮食摄入与PP的相互联系,以完善PP的预防策略,为控制儿童PP发病率和年轻化趋势做出理论支撑。

2. 资料与方法

2.1. 实验设计

Figure 1. Schematic diagram of TSMR study hypothesis

1. TSMR研究假设示意图

TSMR使用遗传变异整合为工具变量(IV)并使用来自观察性研究的汇总数据评估暴露与结果之间的关联来确定风险因素与结局之间的观察性关联是否与因果效应一致。由于受孕过程中等位基因的随机分配,遗传变异与疾病结果之间的关系不容易受到环境和混杂因素的影响[13] [14]

基于TSMR分析,我们评估了饮食摄入和PP之间的因果关系。TSMR利用遗传变异来代表风险因素,对于因果推理中的有效工具变量(IVs),必须满足三个关键假设:(1) 遗传变异与暴露直接相关;(2) 遗传变异与暴露与结果之间的潜在混杂因素无关;(3) 遗传变异仅通过暴露影响结果,而不是通过其他途径影响结果。这些假设是确保TSMR分析的有效性的基础(图1)。

2.2. 饮食习惯的GWAS数据汇总

关于饮食摄入的数据来自UKB,这项研究利用了231种不同饮食摄入类型的数据,统计了广泛的营养习惯和食物消费模式。UKB是一个大规模的生物医学数据库和研究资源,涉及来自英国各地的约454,375名参与者的基因、生活方式、健康信息和生物样本。

2.3. 性早熟的GWAS数据汇总

关于PP的数据来自FinnGen,包括152例和434,894例对照。FinnGen是一项大型生物库研究,旨在对500,000名芬兰人的基因型进行分类,芬兰的数据集拥有全面的国家卫生记录,允许精确的病例识别和控制选择。大的对照组确保了检测潜在的因果效应的稳健的统计能力。此外,芬兰人口的人口统计学和遗传同质性提高了本研究中确定的遗传关联的可靠性,减少了人群分层混淆的可能性。

2.4. 工具变量(IVs)的选择

由于遗传变异与暴露之间的直接相关性,我们将每种膳食摄入量的显著性水平设为1 × 105。为了获得独立的位点IV,我们使用了一个设置为R2 < 0.001的连锁不平衡(LD)阈值,聚合距离为10,000 kb。对于PP,我们将显著性水平调整为5 × 105,LD阈值为R2 < 0.001,聚集距离为10,000 kb。计算单个SNP的F值,并排除F < 10的SNP。

2.5. TSMR分析

所有的分析都使用R软件版本4.3.3进行,这是一个统计计算和图形可视化的综合环境,在R软件中设置“TwoSampleMR”软件包(0.5.7版本),该软件包用于估计因果效应、进行假设检验和执行敏感性分析,以及验证研究结果的稳健性。

本研究中采用的因果估计的主要方法是IVW法,IVW法是MR中的一种标准方法,它结合了来自多个遗传变异的Wald估计值(SNP结果关联与SNP暴露关联的比值),并通过与每个SNP结果相关的逆方差进行加权。然后使用加权平均值将这些估计进行组合,其中权重由与每个SNP结果效应相关的方差的倒数决定。当所有的工具变量都满足TSMR假设时,这种方法在产生因果效应的精确估计方面特别有效。Weighted median法、Mode-based法可以作为补充方法,即使某些工具变量无效,只要满足一定的假设,也可以提供稳健的因果估计。

2.6. 敏感性分析

敏感性分析包括异质性检验、水平多效性检验和逐个剔除检验。为了保证结果的可靠性和准确性,我们运用Cochran’s Q检验,以检验工具变量之间的异质性。异质性指的是来自不同工具的因果估计的可变性,这可能表明违反了MR假设或存在多效性(其中一个遗传变异影响多个性状)。通过检验异质性来验证不同工具之间的因果估计的一致性。多效性检验使用MR-Egger回归和MRPRESSO方法,使用MR-Egger截距评估水平多效性,当基因变异通过暴露以外的途径影响结果时,就会发生一个遗传变异影响多个性状的情况。由以上数据p值 > 0.05,MR-Egger检验的结果显示没有显著的水平多效性,这表明多效性不太可能对结果产生偏差,符合排他性假设。此外,MRPRESSO分析用于检测并尝试通过排除显著异常值来降低水平多效性。排除异常值后,再次进行TSMR分析。虽然该测试普遍支持这些研究结果的稳健性,但它在分析李子摄入量和PP的关系中发现存在了水平多效性(p < 0.05),故这些具体结果的可靠性可持怀疑态度。经MRPRESSO校正的两个异常值都被标记为不适用(NA),这表明在这些特定分析中可能存在的问题,应谨慎解释。使用Leave one out法分析评估单一SNP对结局的影响。如果有离群值需要去掉后重新分析,本研究显示无个别SNP对整体因果关系预测产生影响。

Figure 2. Positive MR analysis of forest map

2. 正向TSMR分析森林图

3. 结果

3.1. 正向TSMR结果

使用IVW方法,将显著性水平设为0.05,确定了10种不同类型的饮食摄入与PP风险之间存在显著的因果关系。然而,经过进一步的分析,由于多种MR方法,包括MR Egger、Weighted median和IVW在效应方向上不一致,我们排除了肉汤摄入。经过这一调整后,分析证实了9种特定的饮食摄入和PP之间存在因果关系。其中,5种饮食摄入表现出正因果关系,即盐渍花生的摄入(ukb-b-1099) (OR = 1480.226, 95% CI = (14.460~151528.425), p = 0.002)、其他咸口小吃的摄入(ukb-b-18718) (OR = 326.312, 95% CI = (2.452~43431.149), p = 0.020)、西梅的摄入(ukb-b-3022) (OR = 1174.199, 95% CI = (6.603~208798.930), p = 0.007)、标准茶摄入量(ukb-b-3291) (OR = 1.011, 95% CI = (1.000~1.022), p = 0.040)以及酒精摄入的频率 (ukb-b-5799) (OR = 3.332, 95% CI = (1.491~7.448), p = 0.003),表明它们可能导致PP发病风险增加;其余4种表现出负因果关系,白鱼的摄入(ukb-b-5427)的摄入(OR = 0.004, 95% CI = (0.000~0.259), p = 0.010)、牛奶布丁的摄入(ukb-b-9857) (OR = 0.002, 95% CI = (0.000~0.297), p = 0.015)、煎饼(ukb-b-6500) (OR = 0.014, 95% CI = (0.000~0.808), p = 0.039)、平均每周摄入烈酒(ukb-b-1707) (OR = 0.039, 95% CI = (0.002~0.624), p = 0.022),即它们在延缓PP的发生方面发挥作用(图2)。

3.2. 反向TSMR的结果

使用IVW方法,将显著性水平设为0.05,探讨反向因果关系,这次以PP为暴露,以各种类型的饮食摄入为结果。通过这一分析,确定了标准茶摄入(ukb-b-3291) (OR = 0.402, 95% CI = (0.169~0.957), p = 0.04)、白鱼的摄入(ukb-b-5427) (OR = 0.998, 95% CI = (0.995~1.000), p = 0.038)与PP之间的反向因果关系。具体来说,患有性早熟可能会影响这些特定饮食项目的摄入量增加或减少的可能性(图3)。这种反向分析为饮食和青春期早期开始之间的双向关系提供了额外的见解,强调了这些因素之间可能存在的潜在反馈机制。

Figure 3. Negative MR analysis of forest map

3. 反向TSMR森林图

4. 讨论

食物和营养都是提供健康饮食的关键。归根结底,人体需要的只是蛋白质、脂肪、维生素、矿物质和碳水化合物。保持它们在体内的水平是健康生活的一个重要考虑因素。它们的不平衡可能会导致体内的各种疾病。世界卫生组织认为:蔬菜,豆类,坚果,种子和水果是健康的食物,而盐,饱和脂肪和过量的含糖食物被认为是致病的[15]。盐渍花生和咸味小吃属于加工产品,主要的问题在于制作过程中加入了大量的盐、糖、油脂等物质。常见的有咸口小吃有薯片、咸味饼干、馅饼、香肠、比萨、热薯条或炸薯条、热狗、加工肉类和外卖食品。NOVA食物分类系统把咸味小吃列为超加工食品之一,认为影响了人类健康[16]。同样,国际粮食政策研究所(IFPRI)列举了许多高度加工食品,并表明这些食物可能大量地添加了糖、脂肪和盐等[17]。大量的研究表明食用超加工食品与肠道微生物紊乱、肥胖、心血管风险因素增加(如血脂异常、高血压)以及乳腺癌等不良健康后果有关[18]。美国的一项研究结果表明,与摄入未加工饮食对比,摄入含有大量超加工食品的饮食会增加能量摄入并导致体重增加[19]。然而,目前的研究已将肥胖确定为PP的危险因素,一项横断面研究评估了具有不同BMI的中国儿童的PP患病率。分析显示,青春期体征与两性BMI呈正相关,且女孩的相关性更高[20]。Rosenfield等人报道也表明BMI高的女孩比BMI低的女孩更早到达月经初潮时期[21]。然而,Zhai等人的一项纵向研究和一些横断面调查表明,青春期前体重过重可能会延迟男孩的性发育[22]。尽管在肥胖对男性PP的影响方面存在争议,但无一例外地证明了肥胖对PP确实存在影响。关于肥胖人群的致病机制,先前已有研究发现肥胖人群的外周信号(如瘦素、脂联素、胰岛素和生长素释放肽水平)能够通过参与HPG轴的调节,进而影响了青春期的时间。如瘦素通过与瘦素受体结合激活kisspeptin通路直接刺激GnRH和促性腺激素分泌;生长素释放肽能抑制kisspeptin表达;脂联素通过AMP激酶途径抑制GnRH神经元的产生;肥胖相关胰岛素抵抗引起的高胰岛素血症可减少肝脏SHBG的产生并提高性类固醇的生物利用度[23]。结合本研究结果,可以推断盐渍花生和咸味小吃的摄入可能首先导致了儿童肥胖,进而导致PP的发生。

西梅/李子中含有大量的黄酮类化合物。黄酮类化合物属于植物雌激素中的一个科,植物雌激素是从植物中提取的天然化学化合物,结构上与动物体内合成的生物雌激素相似,故食用植物雌激素可带来与人类雌激素类似的后果(雌激素效应)或相反的效应(抗雌激素效应),但最终所造成的结果还取决于当下体内雌激素的水平以及植物雌激素与体内受体结合的方式[24]。黄酮类化合物中最主要的是黄酮醇(如槲皮素、山奈酚和杨梅素),大量存在于各种水果、绿叶蔬菜、洋葱和茶中[25]。下丘脑中的Kisspeptin信号系统参与HPG轴的整合,促进生殖成熟。研究发现异黄酮,其生物合成可能影响kisspeptin信号通路,这可能成为女性PP的基础[26];Kim等人通过109例CPP患儿的病例对照研究发现CPP患儿的血清异黄酮浓度较高[27];Marks等人通过记录367位母亲在怀孕期间接触植物雌激素的情况,并研究她们与女儿月经初潮年龄的关系发现孕妇摄入植物雌激素与其后代月经初潮较早之间存在明显的联系[28]。这些研究结果与本研究结论一致,都支持了含黄酮类化合物的食物摄入是PP发病的危险因素。然而,Cheng等人的研究发现儿童时期高异黄酮饮食的女孩比低异黄酮饮食的女孩青春期推迟了7个月,因此猜测异黄酮有延迟青春期的作用[29]。这些不同案例研究的观察性结果存在较大的差异,因此有必要进一步进行更大样本量、多中心的研究,以期获得推荐的摄入水平及时机。

茶被视为世界三大饮料之一,茶中富含咖啡因、茶多酚、抗坏血酸盐等物质,探讨茶对PP的影响,应该就其中的具体成分来展开研究。许多动物实验研究和人类病例对照研究都指出咖啡因对生殖系统具有毒性作用,这与本研究结果方向一致。在一项动物实验中报道,不论多大浓度的咖啡因,始终能诱导雌二醇分泌增加,特定浓度下还会引起乳腺的发育[30];此外,在男性和雄兔中也记录了咖啡因摄入量较高时睾酮的增加[31] [32];研究证明青春期前后的咖啡因暴露会影响未成熟大鼠睾酮、雌二醇的产生[33] [34]。青春期性腺在解剖学或组织化学上都没有完全成熟,因此,如果在这个脆弱时期长期接触咖啡因会干扰正常的性腺成熟。然而,与本研究结论相悖的是茶中的茶多酚被证明能够改善PP的影响。一项双盲随机对照试验发现脱咖啡因绿茶多酚(DGTP)能够有效预防肥胖女孩发生PP [35];动物实验发现绿茶中的表没食子儿茶素没食子酸酯(ECGC)可以通过NKB/NK3R信号通路预防肥胖相关的PP [35]。结合本研究结果,是否通过限制茶的摄入来控制PP的发生,须进一步根据茶的成分差异开展研究。

酒精饮品摄入频率及平均每周摄入烈酒两个因素的共同点在于酒精,区别在于酒精含量。本研究结果表明酒精对PP可发挥促进或延缓作用,与先前研究相符:丹麦一项研究观察到母亲妊娠早期暴露于酒精,其女儿可以观察到青春期提前的趋势[36]。而Peck等人的横断面研究发现青春期前饮酒的女孩青春期延迟的几率是非暴露者的四倍[37];几项动物研究发现其机制在于酒精可以通过抑制IGF-1受体诱导的磷酸化、刺激Dyn释放,从而抑制kisspeptin和GnRH的合成及分泌[38]-[40]。基于先前研究结果的差异性,未来的研究应考虑酒精浓度、酒精饮料类型、短期或长期暴露、暴露剂量、暴露年龄、暴露性别等之间的关系进行更深入的研究,且由于酒精具有一定的神经毒性,在忽略剂量–效应的前提下,不建议推荐给正在发育的儿童及青少年饮用。

鱼中含有丰富的ω-3多不饱和脂肪酸(PUFAs),特别是二十碳五烯酸(EPA)和二十二碳六烯酸(DHA)。在一项前瞻性研究中发现金枪鱼/沙丁鱼摄入量较高的女孩初潮年龄显著推迟[41],潜在机制可能被与金枪鱼/沙丁鱼中富含长链PUFA,更有利于心血管状况及体重增长较慢[42] [43]。一项动物实验发现随着围产期n-6 PUFA摄入量的增加,小鼠的青春期开始延迟[44]。另一项针对100名13岁儿童的丹麦研究发现,在哺乳期的前4个月补充一定量的EPA和DHA,与男孩的青春期成熟较晚之间存在关联[45]。故我们推荐摄入一定量的鱼类以改善PP的趋势,一些特定的白鱼品种,如鳕鱼,不仅脂肪较少,但n-3 LCFA含量高,重金属污染物含量低[46],更值得推荐食用。

牛奶布丁属于乳制品中的一种,其他的乳制品还有调味牛奶、酸奶和奶酪及其他乳制品甜点等。发达国家的一项研究发现青少年中,乳制品摄入量与肥胖呈负相关[47],然而肥胖是PP的风险因素,我们猜测乳制品能因其对肥胖的抑制作用,间接产生抑制PP发生的结果。一项针对美国女孩的研究显示,5至12岁女孩的牛奶摄入频率与月经初潮年龄呈负相关[48]。一项针对智利女孩的研究显示酸奶摄入量较高的女孩月经初潮年龄延迟,这些研究结果与本研究结论一致。然而,也有一些研究主张乳制品的摄入会引发PP或无关[49] [50]。故还需要进行更多的研究,以调查不同时期乳制品消费模式是否会影响青春期。

烙饼/煎饼是是一种以面糊形式在烤盘或平底锅上烹饪制成的薄扁状饼,因其便捷的烹饪形式及健康的原材料在许多国家都深受欢迎。其原材料主要是各种谷物面粉(如荞麦粉、小麦粉、玉米粉、土豆粉等),辅以鸡蛋、牛奶、水、果酱、蔬菜及酵母等,很少含有肉类。中国、美国、澳大利亚、加拿大等多个国家都在膳食指南中强调了谷物摄入的比例及重要性。尽管目前缺乏单一食用煎饼与PP直接的观察性研究,但已有调查发现与不食用谷物的人相比,儿童和青少年食用含量不等的谷物食物更有利于生长发育[51]。谷物中最大的优点在于含有丰富的膳食纤维,可以增强饱腹感,减少其他食物的摄入,与等量的精制谷物相比更有助于控制体重[52],这也间接减少儿童肥胖的几率。

5. 结论

总之,我们发现摄入盐渍花生、咸口小吃、西梅及茶是PP的危险因素,而摄入白鱼类、牛奶布丁、烙饼/煎饼有助于降低PP的发病率。关于酒精对PP发挥的双面效应有待进一步探索。此外,我们的研究首次发现了患有PP的儿童在茶、白鱼类的摄入有倾向性,需要进行更多的实验以验证人类饮食的偏好与机体疾病之间是否存在一定的反馈机制。我们的研究结果为理解PP的发病机制提供了新的线索,重点关注特殊的会引起PP的饮食摄入,为健康儿童及合并性早熟高危因素的儿童提供饮食指导及干预,以期降低PP的发病率及年轻化趋势。

参考文献

[1] Cheuiche, A.V., da Silveira, L.G., de Paula, L.C.P., Lucena, I.R.S. and Silveiro, S.P. (2021) Diagnosis and Management of Precocious Sexual Maturation: An Updated Review. European Journal of Pediatrics, 180, 3073-3087.
https://doi.org/10.1007/s00431-021-04022-1
[2] Knobil, E. (1980) The Neuroendocrine Control of the Menstrual Cycle. Recent Progress in Hormone Research, 36, 53-88.
https://doi.org/10.1016/b978-0-12-571136-4.50008-5
[3] Latronico, A.C., Brito, V.N. and Carel, J. (2016) Causes, Diagnosis, and Treatment of Central Precocious Puberty. The Lancet Diabetes & Endocrinology, 4, 265-274.
https://doi.org/10.1016/s2213-8587(15)00380-0
[4] Cantas-Orsdemir, S. and Eugster, E.A. (2019) Update on Central Precocious Puberty: From Etiologies to Outcomes. Expert Review of Endocrinology & Metabolism, 14, 123-130.
https://doi.org/10.1080/17446651.2019.1575726
[5] Teilmann, G., Pedersen, C.B., Jensen, T.K., Skakkebæk, N.E. and Juul, A. (2005) Prevalence and Incidence of Precocious Pubertal Development in Denmark: An Epidemiologic Study Based on National Registries. Pediatrics, 116, 1323-1328.
https://doi.org/10.1542/peds.2005-0012
[6] Kim, S.H., Huh, K., Won, S., Lee, K. and Park, M. (2015) A Significant Increase in the Incidence of Central Precocious Puberty among Korean Girls from 2004 to 2010. PLOS ONE, 10, e0141844.
https://doi.org/10.1371/journal.pone.0141844
[7] Soriano-Guillén, L., Corripio, R., Labarta, J.I., Cañete, R., Castro-Feijóo, L., Espino, R., et al. (2010) Central Precocious Puberty in Children Living in Spain: Incidence, Prevalence, and Influence of Adoption and Immigration. The Journal of Clinical Endocrinology & Metabolism, 95, 4305-4313.
https://doi.org/10.1210/jc.2010-1025
[8] Tenedero, C.B., Oei, K. and Palmert, M.R. (2021) An Approach to the Evaluation and Management of the Obese Child with Early Puberty. Journal of the Endocrine Society, 6, bvab173.
https://doi.org/10.1210/jendso/bvab173
[9] Sultan, C., Gaspari, L., Kalfa, N. and Paris, F. (2012) Clinical Expression of Precocious Puberty in Girls. In: Sultan, C., Ed., Endocrine Development, S. Karger AG, 84-100.
https://doi.org/10.1159/000334304
[10] Eckert-Lind, C., Busch, A.S., Petersen, J.H., Biro, F.M., Butler, G., Bräuner, E.V., et al. (2020) Worldwide Secular Trends in Age at Pubertal Onset Assessed by Breast Development among Girls: A Systematic Review and Meta-Analysis. JAMA Pediatrics, 174, e195881.
https://doi.org/10.1001/jamapediatrics.2019.5881
[11] Biro, F.M., Galvez, M.P., Greenspan, L.C., Succop, P.A., Vangeepuram, N., Pinney, S.M., et al. (2010) Pubertal Assessment Method and Baseline Characteristics in a Mixed Longitudinal Study of Girls. Pediatrics, 126, e583-e590.
https://doi.org/10.1542/peds.2009-3079
[12] Karlberg, J. (2002) Secular Trends in Pubertal Development. Hormone Research in Paediatrics, 57, 19-30.
https://doi.org/10.1159/000058096
[13] Davey Smith, G. and Hemani, G. (2014) Mendelian Randomization: Genetic Anchors for Causal Inference in Epidemiological Studies. Human Molecular Genetics, 23, R89-R98.
https://doi.org/10.1093/hmg/ddu328
[14] Emdin, C.A., Khera, A.V. and Kathiresan, S. (2017) Mendelian Randomization. JAMA, 318, 1925-1926.
https://doi.org/10.1001/jama.2017.17219
[15] Song, M., Fung, T.T., Hu, F.B., Willett, W.C., Longo, V.D., Chan, A.T., et al. (2016) Association of Animal and Plant Protein Intake with All-Cause and Cause-Specific Mortality. JAMA Internal Medicine, 176, 1453-1463.
https://doi.org/10.1001/jamainternmed.2016.4182
[16] Lawrence, M.A. and Baker, P.I. (2019) Ultra-processed Food and Adverse Health Outcomes. BMJ, 365, L2289.
https://doi.org/10.1136/bmj.l2289
[17] Asfaw, A. (2011) Does Consumption of Processed Foods Explain Disparities in the Body Weight of Individuals? The Case of Guatemala. Health Economics, 20, 184-195.
https://doi.org/10.1002/hec.1579
[18] Monteiro, C.A., Cannon, G., Levy, R.B., Moubarac, J., Louzada, M.L., Rauber, F., et al. (2019) Ultra-Processed Foods: What They Are and How to Identify Them. Public Health Nutrition, 22, 936-941.
https://doi.org/10.1017/s1368980018003762
[19] Hall, K.D., Ayuketah, A., Brychta, R., Cai, H., Cassimatis, T., Chen, K.Y., et al. (2019) Ultra-Processed Diets Cause Excess Calorie Intake and Weight Gain: An Inpatient Randomized Controlled Trial of Ad Libitum Food Intake. Cell Metabolism, 30, 67-77.e3.
https://doi.org/10.1016/j.cmet.2019.05.008
[20] Liu, M., Cao, B., Luo, Q., Wang, Q., Liu, M., Liang, X., et al. (2022) The Critical BMI Hypothesis for Puberty Initiation and the Gender Prevalence Difference: Evidence from an Epidemiological Survey in Beijing, China. Frontiers in Endocrinology, 13, Article 1009133.
https://doi.org/10.3389/fendo.2022.1009133
[21] Rosenfield, R.L., Lipton, R.B. and Drum, M.L. (2009) Thelarche, Pubarche, and Menarche Attainment in Children with Normal and Elevated Body Mass Index. Pediatrics, 123, 84-88.
https://doi.org/10.1542/peds.2008-0146
[22] Lee, S.Y., Kim, J.M., Kim, Y.M. and Lim, H.H. (2021) Single Random Measurement of Urinary Gonadotropin Concentration for Screening and Monitoring Girls with Central Precocious Puberty. Annals of Pediatric Endocrinology & Metabolism, 26, 178-184.
https://doi.org/10.6065/apem.2040208.104
[23] Calcaterra, V., Magenes, V.C., Hruby, C., Siccardo, F., Mari, A., Cordaro, E., et al. (2023) Links between Childhood Obesity, High-Fat Diet, and Central Precocious Puberty. Children, 10, Article 241.
https://doi.org/10.3390/children10020241
[24] Bhattacharya, S. and nee Paul, S.M. (2021) Phytoestrogens Responsible for Altered Pubertal Timing in Females: A Matter of Concern. Proceedings of the Zoological Society, 74, 558-571.
https://doi.org/10.1007/s12595-021-00398-y
[25] Hertog, M.G.L., Feskens, E.J.M., Hollman, P.C.H., Katan, M.B. and Kromhout, D. (1994) Dietary Flavonoids and Cancer Risk in the Zutphen Elderly Study. Nutrition and Cancer, 22, 175-184.
https://doi.org/10.1080/01635589409514342
[26] Patisaul, H.B. (2013) Effects of Environmental Endocrine Disruptors and Phytoestrogens on the Kisspeptin System. In: Kauffman, A. and Smith, J., Eds, Kisspeptin Signaling in Reproductive Biology, Springer, 455-479.
https://doi.org/10.1007/978-1-4614-6199-9_21
[27] Kim, J., Kim, S., Huh, K., Kim, Y., Joung, H. and Park, M. (2011) High Serum Isoflavone Concentrations Are Associated with the Risk of Precocious Puberty in Korean Girls. Clinical Endocrinology, 75, 831-835.
https://doi.org/10.1111/j.1365-2265.2011.04127.x
[28] Marks, K.J., Hartman, T.J., Taylor, E.V., Rybak, M.E., Northstone, K. and Marcus, M. (2017) Exposure to Phytoestrogens in Utero and Age at Menarche in a Contemporary British Cohort. Environmental Research, 155, 287-293.
https://doi.org/10.1016/j.envres.2017.02.030
[29] Cheng, G., Remer, T., Prinz-Langenohl, R., Blaszkewicz, M., Degen, G.H. and Buyken, A.E. (2010) Relation of Isoflavones and Fiber Intake in Childhood to the Timing of Puberty. The American Journal of Clinical Nutrition, 92, 556-564.
https://doi.org/10.3945/ajcn.2010.29394
[30] Tinwell, H., Colombel, S., Blanck, O. and Bars, R. (2013) The Screening of Everyday Life Chemicals in Validated Assays Targeting the Pituitary-Gonadal Axis. Regulatory Toxicology and Pharmacology, 66, 184-196.
https://doi.org/10.1016/j.yrtph.2013.04.002
[31] Wedick, N.M., Mantzoros, C.S., Ding, E.L., Brennan, A.M., Rosner, B., Rimm, E.B., et al. (2012) The Effects of Caffeinated and Decaffeinated Coffee on Sex Hormone-Binding Globulin and Endogenous Sex Hormone Levels: A Randomized Controlled Trial. Nutrition Journal, 11, Article No. 86.
https://doi.org/10.1186/1475-2891-11-86
[32] Ezzat, A.R. and El-Gohary, Z.M. (1994) Hormonal and Histological Effects of Chronic Caffeine Administration on the Pituitary-Gonadal and Pituitary-Adrenocortical Axes in Male Rabbits. Functional and Developmental Morphology, 4, 45-50.
[33] Park, M., Choi, Y., Choi, H., Yim, J. and Roh, J. (2015) High Doses of Caffeine during the Peripubertal Period in the Rat Impair the Growth and Function of the Testis. International Journal of Endocrinology, 2015, Article ID: 368475.
https://doi.org/10.1155/2015/368475
[34] Xie, L., Tang, Q., Yao, D., Gu, Q., Zheng, H., Wang, X., et al. (2021) Effect of Decaffeinated Green Tea Polyphenols on Body Fat and Precocious Puberty in Obese Girls: A Randomized Controlled Trial. Frontiers in Endocrinology, 12, Article ID: 736724.
https://doi.org/10.3389/fendo.2021.736724
[35] Gu, Q., Wang, X., Xie, L., Yao, X., Qian, L., Yu, Z., et al. (2022) Green Tea Catechin EGCG Could Prevent Obesity-Related Precocious Puberty through NKB/NK3R Signaling Pathway. The Journal of Nutritional Biochemistry, 108, Article ID: 109085.
https://doi.org/10.1016/j.jnutbio.2022.109085
[36] Brix, N., Lauridsen, L.L.B., Ernst, A., Olsen, J., Henriksen, T.B. and Ramlau-Hansen, C.H. (2020) Alcohol Intake during Pregnancy and Timing of Puberty in Sons and Daughters: A Nationwide Cohort Study. Reproductive Toxicology, 91, 35-42.
https://doi.org/10.1016/j.reprotox.2019.11.003
[37] Peck, J.D., Peck, B.M., Skaggs, V.J., Fukushima, M. and Kaplan, H.B. (2011) Socio-Environmental Factors Associated with Pubertal Development in Female Adolescents: The Role of Prepubertal Tobacco and Alcohol Use. Journal of Adolescent Health, 48, 241-246.
https://doi.org/10.1016/j.jadohealth.2010.06.018
[38] Hiney, J.K., Srivastava, V.K. and Les Dees, W. (2010) Insulin-like Growth Factor-1 Stimulation of Hypothalamic Kiss-1 Gene Expression Is Mediated by Akt: Effect of Alcohol. Neuroscience, 166, 625-632.
https://doi.org/10.1016/j.neuroscience.2009.12.030
[39] Dees, W.L., Hiney, J.K. and Srivastava, V.K. (2017) Alcohol and Puberty: Mechanisms of Delayed Development. Alcohol Research: Current Reviews, 38, 277-282.
[40] Srivastava, V.K., Hiney, J.K., Stevener, K. and Dees, W.L. (2015) Differential Effects of Alcohol on Excitatory and Inhibitory Puberty‐Related Peptides in the Basal Hypothalamus of the Female Rat. Alcoholism: Clinical and Experimental Research, 39, 2386-2393.
https://doi.org/10.1111/acer.12905
[41] Jansen, E.C., Marín, C., Mora-Plazas, M. and Villamor, E. (2016) Higher Childhood Red Meat Intake Frequency Is Associated with Earlier Age at Menarche. The Journal of Nutrition, 146, 792-798.
https://doi.org/10.3945/jn.115.226456
[42] Bonafini, S., Antoniazzi, F., Maffeis, C., Minuz, P. and Fava, C. (2015) Beneficial Effects of ω-3 PUFA in Children on Cardiovascular Risk Factors during Childhood and Adolescence. Prostaglandins & Other Lipid Mediators, 120, 72-79.
https://doi.org/10.1016/j.prostaglandins.2015.03.006
[43] Perng, W., Villamor, E., Mora-Plazas, M., Marin, C. and Baylin, A. (2014) α-Linolenic Acid (ALA) Is Inversely Related to Development of Adiposity in School-Age Children. European Journal of Clinical Nutrition, 69, 167-172.
https://doi.org/10.1038/ejcn.2014.210
[44] Lauritzen, L., Eriksen, S.E., Hjorth, M.F., Nielsen, M.S., Olsen, S.F., Stark, K.D., et al. (2016) Maternal Fish Oil Supplementation during Lactation Is Associated with Reduced Height at 13 Years of Age and Higher Blood Pressure in Boys Only. British Journal of Nutrition, 116, 2082-2090.
https://doi.org/10.1017/s0007114516004293
[45] Santillán, M.E., Vincenti, L.M., Martini, A.C., Fiol de Cuneo, M., Ruiz, R.D., Mangeaud, A., et al. (2010) Developmental and Neurobehavioral Effects of Perinatal Exposure to Diets with Different Ω-6:ω-3 Ratios in Mice. Nutrition, 26, 423-431.
https://doi.org/10.1016/j.nut.2009.06.005
[46] Vázquez, C., Botella-Carretero, J.I., Corella, D., Fiol, M., Lage, M., Lurbe, E., et al. (2014) White Fish Reduces Cardiovascular Risk Factors in Patients with Metabolic Syndrome: The WISH-CARE Study, a Multicenter Randomized Clinical Trial. Nutrition, Metabolism and Cardiovascular Diseases, 24, 328-335.
https://doi.org/10.1016/j.numecd.2013.09.018
[47] Dror, D.K. (2014) Dairy Consumption and Pre‐School, School‐Age and Adolescent Obesity in Developed Countries: A Systematic Review and Meta‐Analysis. Obesity Reviews, 15, 516-527.
https://doi.org/10.1111/obr.12158
[48] Wiley, A.S. (2011) Milk Intake and Total Dairy Consumption: Associations with Early Menarche in NHANES 1999-2004. PLOS ONE, 6, e14685.
https://doi.org/10.1371/journal.pone.0014685
[49] Ramezani Tehrani, F., Moslehi, N., Asghari, G., Gholami, R., Mirmiran, P. and Azizi, F. (2013) Intake of Dairy Products, Calcium, Magnesium, and Phosphorus in Childhood and Age at Menarche in the Tehran Lipid and Glucose Study. PLOS ONE, 8, e57696.
https://doi.org/10.1371/journal.pone.0057696
[50] Carwile, J.L., Willett, W.C., Wang, M., Rich-Edwards, J., Frazier, A.L. and Michels, K.B. (2015) Milk Consumption after Age 9 Years Does Not Predict Age at Menarche. The Journal of Nutrition, 145, 1900-1908.
https://doi.org/10.3945/jn.115.214270
[51] Papanikolaou, Y., Jones, J.M. and Fulgoni, V.L. (2017) Several Grain Dietary Patterns Are Associated with Better Diet Quality and Improved Shortfall Nutrient Intakes in US Children and Adolescents: A Study Focusing on the 2015-2020 Dietary Guidelines for Americans. Nutrition Journal, 16, Article No. 13.
https://doi.org/10.1186/s12937-017-0230-0
[52] Kissock, K.R., Neale, E.P. and Beck, E.J. (2021) Whole Grain Food Definition Effects on Determining Associations of Whole Grain Intake and Body Weight Changes: A Systematic Review. Advances in Nutrition, 12, 693-707.
https://doi.org/10.1093/advances/nmaa122